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1

Motais de Narbonne, Anne-Marie. "Resource Sharing: Information Sharing." International Astronomical Union Colloquium 110 (1989): 198. http://dx.doi.org/10.1017/s0252921100003407.

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When we speak of resource sharing, we mostly mean document sharing through union catalogues, list exchanges, interlibrary loans, cooperative acquisition programs... Yet, the first and primary condition of the library network efficiency is information sharing.Libraries have been quite successful in this field for the last decades but, nowadays, new technology such as electronic mail or telefax offers unequaled facilities to set up and promote a permanent and world wide program of information exchanges liable to meet the increasing needs of punctual responses. From an eight year experience at Paris Observatory library which has been hosting the French national service CADIST [Centre d’acquisition et d’information scientifique et technique], we can assert that, outer demands of informations being at the same time useful information sources, such a quick answer service does participate to the improvement of the inner service efficiency.
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Eaton, Nancy L. "Resource Sharing:." Journal of Library Administration 21, no. 1-2 (November 1995): 27–38. http://dx.doi.org/10.1300/j111v21n01_03.

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Degkwitz, Andreas. "Resource Sharing:." Serials Librarian 29, no. 1-2 (June 1996): 205–17. http://dx.doi.org/10.1300/j123v29n01_12.

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Baker, Barry B. "Resource Sharing." Technical Services Quarterly 16, no. 2 (December 4, 1998): 35–45. http://dx.doi.org/10.1300/j124v16n02_04.

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Baker, Shirley K. "Resource Sharing." Technical Services Quarterly 16, no. 2 (December 4, 1998): 47–56. http://dx.doi.org/10.1300/j124v16n02_05.

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6

Varma, P. C. V. "Resource sharing." IEEE Potentials 23, no. 5 (January 2005): 14–16. http://dx.doi.org/10.1109/mp.2005.1368911.

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7

Kumbhar, Mrs Anuradha A. "Resource Sharing and Networking in Libraries." International Journal of Trend in Scientific Research and Development Special Issue, Special Issue-ICDEBI2018 (October 3, 2018): 224–27. http://dx.doi.org/10.31142/ijtsrd18709.

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8

St. Clair, Gloriana. "Editorial: Resource Sharing." College & Research Libraries 52, no. 2 (March 1, 1991): 115–16. http://dx.doi.org/10.5860/crl_52_02_115.

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9

Wallhaus, Robert. "Library Resource Sharing." Resource Sharing & Information Networks 2, no. 3-4 (February 18, 1986): 11–19. http://dx.doi.org/10.1300/j121v02n03_04.

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Dumont, Paul E. "Library Resource Sharing." Resource Sharing & Information Networks 16, no. 1 (January 2002): 133–44. http://dx.doi.org/10.1300/j121v16n01_10.

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McCluskey, Margaret. "Global Resource Sharing." Australian Academic & Research Libraries 44, no. 3 (September 2013): 187–88. http://dx.doi.org/10.1080/00048623.2013.817287.

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Beaubien, Anne K., and Patricia Stevens. "Rethinking Resource Sharing." Resource Sharing & Information Networks 19, no. 1-2 (December 18, 2008): 3–14. http://dx.doi.org/10.1080/07377790802308581.

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13

De Lisle, Harold F. "Sharing the Resource." Reptiles & Amphibians 17, no. 1 (March 1, 2010): 42–45. http://dx.doi.org/10.17161/randa.v17i1.16065.

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The competitive exclusion principle would seem to apply to six species of rattlesnakes in the genus Crotalus, all of which feed mostly on small mammals. In Joshua Tree National Park, California, however, six species occur in an area of just 400,000 ha. A pattern noted in ecology is that diversity at one level begets diversity at other levels. Almost 70 years of locality data combined with present field research was used as evidence for the hypothesis that these rattlesnake species mostly avoid competitive exclusion by microhabitat differences within the great diversity of ecological communities in the park. These long-term records might also indicate that the dynamics of the desert ecosystem could be changing, possibly the result of climate change and/or local urbanization.
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Kamble, Sangeeta. "Networking and Resource Sharing in Academic Libraries." Journal of Advanced Research in Library and Information Science 05, no. 02 (May 25, 2018): 21–23. http://dx.doi.org/10.24321/2395.2288.201809.

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Kumar, Dr Pardeep, Dr Anbarsu V, Dr Vijayalakshmi and R, and Dr Vengatesan K. "Intellectual Resource Sharing Scheme in Cloud Environment." Journal of Advanced Research in Dynamical and Control Systems 11, no. 10-SPECIAL ISSUE (October 25, 2019): 7–12. http://dx.doi.org/10.5373/jardcs/v11sp10/20192771.

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16

Bredereck, Robert, Andrzej Kaczmarczyk, Junjie Luo, Rolf Niedermeier, and Florian Sachse. "Improving Resource Allocations by Sharing in Pairs." Journal of Artificial Intelligence Research 78 (December 20, 2023): 1069–109. http://dx.doi.org/10.1613/jair.1.15001.

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Given an initial resource allocation, where some agents may envy others or where a different distribution of resources might lead to a higher social welfare, our goal is to improve the allocation without reassigning resources. We consider a sharing concept allowing resources being shared with social network neighbors of the resource owners. More precisely, our model allows agents to form pairs which then may share a limited number of resources. Sharing a resource can come at some costs or loss in utility. To this end, we introduce a formal model that allows a central authority to compute an optimal sharing between neighbors based on an initial allocation. Advocating this point of view, we focus on the most basic scenario where each agent can participate in a bounded number of sharings. We present algorithms for optimizing utilitarian and egalitarian social welfare of allocations and for reducing the number of envious agents. In particular, we examine the computational complexity with respect to several natural parameters. Furthermore, we study cases with restricted social network structures and, among others, devise polynomial-time algorithms in path- and tree-like (hierarchical) social networks.
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Hogan, Sean, Amy R. Paulus, Heather Hannan, and Kim Wobick. "Resource Sharing Resources during a Pandemic: A Review." Journal of Interlibrary Loan, Document Delivery & Electronic Reserve 29, no. 3-5 (October 19, 2020): 139–43. http://dx.doi.org/10.1080/1072303x.2021.1934221.

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18

Bredereck, Robert, Andrzej Kaczmarczyk, Junjie Luo, Rolf Niedermeier, and Florian Sachse. "On Improving Resource Allocations by Sharing." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 5 (June 28, 2022): 4875–83. http://dx.doi.org/10.1609/aaai.v36i5.20416.

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Given an initial resource allocation, where some agents may envy others or where a different distribution of resources might lead to higher social welfare, our goal is to improve the allocation without reassigning resources. We consider a sharing concept allowing resources being shared with social network neighbors of the resource owners. To this end, we introduce a formal model that allows a central authority to compute an optimal sharing between neighbors based on an initial allocation. Advocating this point of view, we focus on the most basic scenario where a resource may be shared by two neighbors in a social network and each agent can participate in a bounded number of sharings. We present algorithms for optimizing utilitarian and egalitarian social welfare of allocations and for reducing the number of envious agents. In particular, we examine the computational complexity with respect to several natural parameters. Furthermore, we study cases with restricted social network structures and, among others, devise polynomial-time algorithms in path- and tree-like (hierarchical) social networks.
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19

Kurokawa, Hidenori, and Hirohiko Kushida. "Resource sharing linear logic." Journal of Logic and Computation 30, no. 1 (January 2020): 295–319. http://dx.doi.org/10.1093/logcom/exaa013.

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Abstract In this paper, we introduce a new logic that we call ‘resource sharing linear logic (RSLL)’. In linear logic (LL), formulas without modality express some resource-conscious situation (a formula can be used only once); formulas with modality express a situation with unlimited resources. We introduce the logic RSLL in which we have a strengthened modality (S5-modality) that can be understood as expressing not only unlimited resources but also resources shared by different agents. Observing that merely strengthening the modality allows weakening axiom to be derivable in a Hilbert-style formulation of this logic, we reformulate RSLL as a logic similar to affine logic by a hypersequent calculus that has weakening as a primitive rule. We prove the completeness of the hypersequent calculus with respect to phase semantics and the cut-elimination theorem for the system by a syntactical method. We also prove the decidability of RSLL via a computational interpretation of RSLL, which is a parallel version of Kopylov’s computational model for LL. We then introduce an explicit counterpart of RSLL in the style of Artemov’s justication logic (JRSLL). We prove a realization theorem for RSLL via its explicit counterpart.
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Chen, Xuejun, and Xiaopeng Ling. "A Conceptual Model Study of Tourism Resource Sharing in the Digital Economy." Sustainability 15, no. 12 (June 19, 2023): 9752. http://dx.doi.org/10.3390/su15129752.

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The concept of “sharing” and the development of the digital economy have driven the transformation of resource allocation in the tourism industry to resource sharing. The article defines resource sharing in the tourism industry from a comprehensive perspective according to the systematic analysis of the concept of resource sharing and the background of the digital economy, which is an economic behavior of integrating, opening and sharing resources among members under the guidance of the government and relying on modern information technology such as the internet, with the sharing of usage rights as the main feature. Based on the dual inspiration of MICK resource classification theory and digital economy theory, the article constructs a conceptual model and measurement scale of resource sharing in the tourism industry from four dimensions: knowledge resource sharing, material resource sharing, information resource sharing and capital resource sharing. The panel data of 31 provinces (municipalities and autonomous regions) from 2016 to 2020 were analyzed mathematically and statistically. The analysis results showed that the weight of knowledge resources is the highest. Moreover, the eastern region had the highest level of resource sharing and the western region had the lowest level of resource sharing. Furthermore, the level of resource sharing in the past five years showed a trend of year-on-year improvement. Based on the scores, countermeasures are proposed in terms of enhancing the importance of information technology and strengthening basic support according to local conditions, which provide a reference for cities to improve the level of resource sharing.
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21

Snyder, Carolyn A., and Beth J. Shapiro. "CIC resource sharing project." College & Research Libraries News 51, no. 1 (January 1, 1990): 21–23. http://dx.doi.org/10.5860/crln.51.1.21.

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22

Rush, James E. "Technology-Driven Resource Sharing." Resource Sharing & Information Networks 8, no. 1 (April 30, 1993): 141–57. http://dx.doi.org/10.1300/j121v08n01_10.

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23

Wittkopf, Barbara J. "Resource Sharing in Louisiana." Resource Sharing & Information Networks 16, no. 1 (January 2002): 103–20. http://dx.doi.org/10.1300/j121v16n01_08.

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24

Gillath, Omri, Ruthann Atchley, Ali Imran, Parnia Haj‐Mohamadi, and Mohamed El‐Hodiri. "Attachment and resource sharing." Personal Relationships 27, no. 2 (May 15, 2020): 228–50. http://dx.doi.org/10.1111/pere.12313.

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25

Simpson, Donald B. "Resource Sharing = Access + Ownership:." Journal of Library Administration 20, no. 1 (March 27, 1995): 95–107. http://dx.doi.org/10.1300/j111v20n01_08.

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26

Getz, Malcolm. "Resource Sharing and Prices." Journal of Library Administration 21, no. 1-2 (November 1995): 77–108. http://dx.doi.org/10.1300/j111v21n01_07.

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27

Hosch, Frederick. "Reprints and resource sharing." 3C ON-LINE 4, no. 1 (January 1997): 7–11. http://dx.doi.org/10.1145/500904.500906.

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28

Parker, J. Stephen. "Superhighways and Resource Sharing." Information Development 11, no. 3 (September 1995): 129. http://dx.doi.org/10.1177/026666699509110301.

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29

Ke, Hao-Ren, and Ruei-Chuan Chang. "Resource sharing digital libraries." Library Collections, Acquisitions, & Technical Services 24, no. 3 (September 2000): 371–77. http://dx.doi.org/10.1080/14649055.2000.10765688.

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30

Mao, Lijun. "Resource Sharing Method of Basic Computer Education Based on Mixed Gaussian Model." Mobile Information Systems 2022 (October 6, 2022): 1–9. http://dx.doi.org/10.1155/2022/6325329.

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This study developed a computer-based basic educational resource sharing method based on a mixed Gaussian model in order to improve the effect of educational resource sharing. Initially, the challenges of educational resource sharing are examined. Then, the basic sharing platform, consisting of the index layer, the computer basic education resource library, and the data layer, is designed. After collecting information about basic computer education resources to be shared, the education resources are clustered using the Gaussian mixture model and then configured based on the results of the clustering. Depending on the number of configuration factors, computer basic education resources can be shared in accordance with their design. The experimental results indicate that this method has high resource sharing efficiency, the ability to update resources in real time, and a good teacher and student evaluation system. Compared to traditional sharing methods, the proposed method has the benefits of a shorter sharing time and greater resource clustering precision.
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31

Tian, Juan. "Information Resources Co-construction and Sharing of Higher Education." Asian Social Science 13, no. 4 (March 24, 2017): 65. http://dx.doi.org/10.5539/ass.v13n4p65.

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With the rapid development of information technology and education, there occurred several problems in higher education information resource construction and sharing, such as incomplete infrastructure, low overall resources level, insufficient information resources application, low teachers' information literacy and imperfect resource sharing mechanism. Under the current environment, it’s necessary to establish a set of information resources co-construction and sharing education service system to balance resources sharing and improve the sharing mechanism. Also to improve colleges’ management, to promote college teachers' development, to adapt to ubiquitous learning and to realize resource sharing.
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Luo, Yang, and Kim Kyung Yee. "Research on Online Education Curriculum Resources Sharing Based on 5G and Internet of Things." Journal of Sensors 2022 (January 5, 2022): 1–10. http://dx.doi.org/10.1155/2022/9675342.

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Information technology has brought great changes to China’s education. 5G technology provides a better guarantee for the sharing of curriculum resources, facing the extreme shortage of educational resources in China. The contradiction between limited educational resources and unlimited development needs of higher education has become increasingly prominent. How to effectively realize resource sharing among universities has become a problem that must be considered in the talent development of universities. In order to solve this problem, universities must improve the utilization rate of resources, maximize resource sharing, and establish a more perfect resource sharing mechanism under the background of 5G and Internet of Things. This paper analyzes the current situation of research at home and abroad, the current situation of resources development, and the application of online courses under the background of Internet of Things, thus constructing an overall framework of curriculum resource sharing mode. According to effective experiments, the offline curriculum education resource sharing and traditional resource sharing schemes in the background of 5G and Internet are compared, and the necessity and importance of applying 5G Internet of Things are verified.
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He, Lanyun. "Ideological and Political Teaching Resource Sharing Method Based on Edge Computing." Wireless Communications and Mobile Computing 2022 (May 2, 2022): 1–10. http://dx.doi.org/10.1155/2022/3907721.

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In the process of ideological and political teaching resource sharing, the sharing time is long due to the interference of redundant data. Therefore, an ideological and political teaching resource sharing method based on edge computing is proposed. Based on the sharing model of ideological and political teaching resources of edge computing, the information entropy suppression method is used to eliminate the redundant data in the ideological and political teaching resources, calculate the sinking of the edge node of the resource after removing the redundancy, assign the task to the edge node, and finally build a location index for the ideological and political teaching resources to realize the sharing of ideological and political teaching resources. The results show that when using the research method to share ideological and political teaching resources, the completion time, average waiting delay, and resource download time of resource sharing are shorter.
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JIANG, Xiaowei, Jingyan Shi, Jiaheng Zou, Qingbao Hu, Ran Du, and Zhenyu Sun. "Research and Exploit of Resource Sharing Strategy at IHEP." EPJ Web of Conferences 214 (2019): 03014. http://dx.doi.org/10.1051/epjconf/201921403014.

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At IHEP (Institute of High Energy Physics, Chinese Academy of Sciences), computing resources are contributed by different experiments including BES, JUNO, DYW, HXMT, etc. The resources were divided into different partitions to satisfy the dedicated experiment data processing requirements. IHEP had a local Torqu&Maui cluster with 50 queues serving for above 10 experiments. The separated resource partitions leaded to imbalance resource load. In a typical situation, BES resource partition was quite busy without free slot but still with lots of jobs in idle, while JUNO resources are free and wasted seriously. After moving resources from Torque&Maui to HTCondor in 2016, job scheduling efficiency has been improved a lot. In order to balance the imbalance resource load, we designed an efficient sharing strategy to improve the overall resourceutilization. We created an unified pool shared by all experiments. For each experiment, resources are divided into two parts: dedicated resource and sharing resource. The slots in dedicated resource only run jobs from its own experiment, and the slots in sharing resource are shared by jobs from all experiments. Default ratio of dedicated resource to sharing resource is 1:4. To maximize the sharing effectiveness, the ratio is dynamically adjusted between 0:5 and 4:1 based on the number of jobs submitted by each experiment. We have developed a central control system to decide how many resources can be allocated to each experiment group. This system is implemented at two sides: server side and client side. A management database is built at server side, which is storing resource, group and experiment information. Once the sharing ratio needs to be adjusted, resource group will be changed and updated into database. The resource group information is published to the server buffer in real-time. The client periodically pulls resource group information from server buffer via https protocol And resource scheduling configuration at client side is changed based on the resource group information. With this method, share ratio can be modified and deployed dynamically. Sharing strategy is implemented with HTCondor. ClassAd mechanism and accounting-group in HTCondor facilitate to utilizethe sharing strategy at IHEP computing cluster. With the sharing strategy, resource usage has been improved dramatically.
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Chen, Li, and Linlin Wang. "Analysis on the Sharing Method of English Mobile Education Resources Based on Wireless Broadband Connection." Wireless Communications and Mobile Computing 2022 (May 9, 2022): 1–8. http://dx.doi.org/10.1155/2022/5166100.

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The sharing of English educational resources has always been a research hotspot in the English industry. The traditional English educational resource sharing system has low resource sharing efficiency and no real-time contribution capability. Therefore, this paper proposes a method to analyze the characteristics of online educational resources. By comparing the main features of the IEEE802 wireless standard series, the IEEE802.16 protocol stack model is constructed by using the IEEE802.16 protocol, the business layer design and CS layer of the English education resource system are realized through the MAC layer and the CPS layer, and the mobile English education resource sharing system is analyzed. Live voting service: in order to improve the sharing speed of mobile English education resources, an NRTPS uplink bandwidth allocation mechanism is proposed, and the design of a mobile English education resource sharing system based on wireless broadband connection is realized. The experimental results show that the resource sharing efficiency of the system is high, and it plays an important role in the development of English education.
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Gastin, Paul, and Dan Teodosiu. "Resource traces: a domain for processes sharing exclusive resources." Theoretical Computer Science 278, no. 1-2 (May 2002): 195–221. http://dx.doi.org/10.1016/s0304-3975(00)00336-4.

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37

Thaker, Khushboo, Yu Chi, Susan Birkhoff, Daqing He, Heidi Donovan, Leah Rosenblum, Peter Brusilovsky, Vivian Hui, and Young Ji Lee. "Exploring Resource-Sharing Behaviors for Finding Relevant Health Resources: Analysis of an Online Ovarian Cancer Community." JMIR Cancer 8, no. 2 (April 12, 2022): e33110. http://dx.doi.org/10.2196/33110.

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Background Online health communities (OHCs) provide patients and survivors of ovarian cancer (OvCa) and their caregivers with help beyond traditional support channels, such as health care providers and clinicians. OvCa OHCs promote connections and exchanges of information among users with similar experiences. Users often exchange information, which leads to the sharing of resources in the form of web links. Although OHCs are important platforms for health management, concerns exist regarding the quality and relevance of shared resources. Previous studies have examined different aspects of resource-sharing behaviors, such as the purpose of sharing, the type of shared resources, and peer user reactions to shared resources in OHCs to evaluate resource exchange scenarios. However, there is a paucity of research examining whether resource-sharing behaviors can ultimately determine the relevance of shared resources. Objective This study aimed to examine the association between OHC resource-sharing behaviors and the relevance of shared resources. We analyzed three aspects of resource-sharing behaviors: types of shared resources, purposes of sharing resources, and OHC users’ reactions to shared resources. Methods Using a retrospective design, data were extracted from the National Ovarian Cancer Coalition discussion forum. The relevance of a resource was classified into three levels: relevant, partially relevant, and not relevant. Resource-sharing behaviors were identified through manual content analysis. A significance test was performed to determine the association between resource relevance and resource-sharing behaviors. Results Approximately 48.3% (85/176) of the shared resources were identified as relevant, 29.5% (52/176) as partially relevant, and 22.2% (39/176) as irrelevant. The study established a significant association between the types of shared resources (χ218=33.2; P<.001) and resource relevance (through chi-square tests of independence). Among the types of shared resources, health consumer materials such as health news (P<.001) and health organizations (P=.02) exhibited significantly more relevant resources. Patient educational materials (P<.001) and patient-generated resources (P=.01) were more significantly associated with partially relevant and irrelevant resources, respectively. Expert health materials, including academic literature, were only shared a few times but had significantly (P<.001) more relevant resources. A significant association (χ210=22.9; P<.001) was also established between the purpose of resource sharing and overall resource relevance. Resources shared with the purpose of providing additional readings (P=.01) and pointing to resources (P=.03) had significantly more relevant resources, whereas subjects for discussion and staying connected did not include any relevant shared resources. Conclusions The associations found between resource-sharing behaviors and the relevance of these resources can help in collecting relevant resources, along with the corresponding information needs from OvCa OHCs, on a large scale through automation. The results from this study can be leveraged to prioritize the resources required by survivors of OvCa and their caregivers, as well as to automate the search for relevant shared resources in OvCa OHCs.
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Feng, Jian, Weiliang Zhang, and Sang-Bing Tsai. "Construction of a Multimedia-Based University Ideological and Political Big Data Cloud Service Teaching Resource Sharing Model." Mathematical Problems in Engineering 2021 (December 29, 2021): 1–12. http://dx.doi.org/10.1155/2021/9907630.

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In this paper, the intelligent education cloud service platform is first constructed in view of the high cost consumption in the process of resource sharing scheduling in colleges and universities. Secondly, the hierarchical education resource sharing grid model is proposed. Specifically, according to the characteristics of the educational resource grid, the key factors affecting the performance of copy creation strategy are analysed, and a dynamic copy creation strategy is proposed. A multiresource equity distribution mechanism based on the concept of resource sharing equity is further proposed. The mechanism establishes a planning model according to the limited task resource demand and the amount of resources shared by the user at different times so that the global cumulative share vector of superior resources meets the dictionary order optimally. The simulation experiment shows that the grid sharing model proposed in this paper has better performance on the educational cloud service platform. The proposed resource allocation mechanism has achieved good results in ensuring the fair distribution of resources and ensuring high resource utilization when resource sharing users put forward multiple groups of time-changing resource demands.
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Wu, Yongli, and Jingliang Chen. "Realization of Mobile Education Resource Sharing Method Based on Wireless Broadband Connection." Scientific Programming 2021 (September 6, 2021): 1–7. http://dx.doi.org/10.1155/2021/4018500.

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Educational resource sharing among students is always an essential component for the development of education level. With the progress of digital and communication networks among institutions, the use and sharing of high-grade educational resources can reach a new level. This paper proposes a new platform for mobile educational resource prediction and sharing via wireless broadband access technology. The architecture of the resource sharing system comprises resource, management, and service layers. An evaluation index system is established to assess the quality of the resource, and a detailed description of the resource assessment methods is presented. Moreover, the social impacts on the allocation of resources and similarities between the social metrics such as response time, success rate, and resource acquisition were investigated. The system has the potential to provide a high success rate and low response time. The system proposed in the paper will stimulate teamwork between teaching groups and increase the ability of resource sharing and optimization more comprehensively.
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Wang, Zhenhong. "Integration and Sharing of College English Teaching Resources Using Cloud Computing Platform." Mobile Information Systems 2022 (April 14, 2022): 1–8. http://dx.doi.org/10.1155/2022/8202229.

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Intelligent computing has been used in the field of education and teaching for a long time in other countries. China is currently conducting education cloud research, but it has not yet been applied to the sharing of instructional resources in universities. The creation of a university instructional resource sharing network based on intelligent computing will help to alleviate the uneven distribution of educational resources to some extent and achieve the goal of high-quality instructional resource sharing, which is critical for improving China’s tertiary education overall. The information age has arrived, thanks to the advancement of information technology and the growth of communication networks. The impact of instructional resources on English classrooms is growing day by day against the backdrop of digitization. The educational resource sharing service platform can effectively deal with the problems of excessive infrastructure investment and low utilization of educational resources with intelligent computing as the technical support. It is essential for promoting educational resource sharing as well as interregional tertiary education exchanges and collaboration. As a result of the research on intelligent computing and educational resource sharing service platform, this paper discusses specific problems such as platform module design, system inspection, and application form, in order to provide a reference for the establishment of educational resource sharing service platform in universities, based on the overall and functional requirements of the platform, a platform that allows teachers and students to access personalized digital resources on demand for reading, downloading, printing, and sharing.
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Anderson, Evan M. "Book Review: Resources Anytime, Anywhere: How Interlibrary Loan becomes Resource Sharing." Library Resources & Technical Services 62, no. 2 (April 4, 2018): 91. http://dx.doi.org/10.5860/lrts.62n2.91.

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At the conclusion of Resources Anytime, Anywhere: How Interlibrary Loan becomes Resource Sharing, the author asks readers to “imagine the future of resource sharing, which is less the sharing of disparate resources between libraries but more of a globally floating library collection” (130). This might seem mere fantasy, but the rapid growth of interlibrary loan (ILL) and progression of technologies used in such services makes the fantasy attainable provided individual libraries, their governing and funding institutions, and the wider public can both adjust to such a situation and find it a desirable vision.
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42

Pei, Yongji, Hailong Wang, Mingxia Li, Xinlei Huang, and Wanmei Geng. "Research and Implementation of Power Grid Resource Information data-sharing Technology." Journal of Physics: Conference Series 2378, no. 1 (December 1, 2022): 012093. http://dx.doi.org/10.1088/1742-6596/2378/1/012093.

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Abstract To avoid the waste of power grid data resources, under the condition of ensuring data security, the design of power grid resource information data-sharing is carried out. Firstly, the security problems that may be encountered in the process of resource sharing are analyzed, and the data resources are encrypted. Then, when that data carries out information interaction between the terminal equipment and the resource sharing cent, the transfer engine is utilized to process the transferred data and transfer the transfer data. Finally, the sharing of data resources is realized by building a calculation model. The experimental results show that the designed information and data-sharing technology consumes less energy on the terminal equipment, and reduces the workload of the terminal equipment for data transmission. It is hoped that the research of this paper can further promote the research of power grid information resource data-sharing.
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43

Dai, Bing, and Xiaoguang An. "Higher Educational Information Resource Sharing Model Based on Blockchain." International Journal of Emerging Technologies in Learning (iJET) 18, no. 07 (April 5, 2023): 72–88. http://dx.doi.org/10.3991/ijet.v18i07.39241.

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Through the sharing of high-quality educational resources in colleges and universities, various colleges and universities have carried out active and effective exchanges in teaching resources, avoiding the duplication of larger educational resources, and improving the academic and career development of teachers and students. The construction of a blockchain-based regional higher education information resource sharing model can solve the problems of scattered teaching resources and duplicate construction of teaching resources, difficulties to ensure the security of digital education resources, high operating costs of platforms, and urgent protection of intellectual property rights of resources. Most of the existing solutions rely on third-party certificate issuing centers or use a single key to encrypt the data flow of education information resources, which has hidden dangers of leakage of privacy information such as intellectual property rights, copyrights, confidential information of resources, other key information, and operation records. Therefore, this paper studies the regional higher education information resource sharing model based on blockchain and designs the data protection protocol of higher education information resources and its resource transaction relationship protection scheme. It introduces the blockchain-based regional higher education information resource sharing model mainly from three aspects: blinding the identity of authorized resource recipients, resource initiators publishing resource transactions, and authorized resource recipients publishing resource transactions. Experimental results verify the effectiveness of the proposed model.
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44

Hua, Xufen. "An Optimization Method for Integrating Educational Information Resources Based on Edge Computing." Journal of Sensors 2022 (July 19, 2022): 1–12. http://dx.doi.org/10.1155/2022/9891117.

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This paper adopts an edge computing approach to conduct in-depth research and analysis on the optimization of educational information resource integration and constructs an integrated teaching resource design model concerning the integrated teaching model, human-centered mobile learning resource design, and the interdisciplinary concept of physics subject teaching method. The learning field constituted by the model is divided into two parts, the explicit field and the potential field and then designs a five-stage teaching resource based on the model. A five-stage teaching resource development path was designed based on the model. Based on the cloud service center model, we propose a hierarchical mechanism for sharing educational information resources and analyze how each hierarchical entity constructs and shares resources and the rights and responsibilities of each hierarchical entity; we explain the meaning and functions of the personalized educational resource integrated development environment provided by the cloud service center for users. The dynamic evaluation model of the value of educational information resources is summarized and proposed for the resource exchange behavior in the sharing of educational information resources, and the significance of the calculation method of resource value, parameter values, and resource value difference for resource sharing is introduced. Firstly, the mechanism for coconstruction of educational information resources at different levels is proposed, and the construction tasks of subjects at different levels in the process of coconstruction and sharing of resources are elaborated. The sharing mechanism of educational information resources covering the regularization system, evaluation mechanism, incentive mechanism, problem handling mechanism, and supporting service mechanism is proposed, and a dynamic evaluation model of the value of educational information resources is designed to improve the enthusiasm of the coconstruction and sharing subjects.
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Guan, Xueming, and Yaozhi Ma. "Wireless Network Virtualization Resource Sharing considering Dynamic Resource Allocation Algorithm." Advances in Multimedia 2022 (August 11, 2022): 1–12. http://dx.doi.org/10.1155/2022/7338309.

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In order to improve the efficiency of wireless network virtualization resource processing, this paper combines the dynamic resource allocation algorithm to construct a wireless network virtualization resource sharing model. This paper proposes a task-oriented resource management model and uses the task-oriented TRS model to describe resources and service processes, reducing the complexity of formulating resource allocation strategies. Moreover, this paper comprehensively considers factors such as centralized coordination control cost and limited domain topology visibility to improve the dynamic resource allocation algorithm. Through comparative research, it can be seen that the wireless network virtualization resource sharing method proposed in this paper considering the dynamic resource allocation algorithm can effectively improve the processing efficiency of wireless network virtualization resources.
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Sloan, Bernard G. "Resource Sharing and System Interconnection." Resource Sharing & Information Networks 8, no. 1 (April 30, 1993): 81–88. http://dx.doi.org/10.1300/j121v08n01_06.

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Poort, Kees. "Resource Sharing and Project Funding." Ecumenical Review 38, no. 4 (October 1986): 431–36. http://dx.doi.org/10.1111/j.1758-6623.1986.tb01375.x.

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48

Leon, Lars, and Nancy Kress. "Looking at resource sharing costs." Interlending & Document Supply 40, no. 2 (May 25, 2012): 81–87. http://dx.doi.org/10.1108/02641611211239542.

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Bakewell, K. G. B. "RESOURCE SHARING: PRACTICE AND PROBLEMS." Library Management 11, no. 3 (March 1990): 2–48. http://dx.doi.org/10.1108/01435129010134880.

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Alqudsi-Ghabra, Taghreed. "Resource Sharing Viability in Kuwait." International Information & Library Review 31, no. 3 (September 1999): 145–56. http://dx.doi.org/10.1080/10572317.1999.10762496.

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