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Journal articles on the topic 'Shared Data Environment'
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Tran, Thi Thu Giang, Duc Quang Le, and Trung Dung Tran. "Virtualization at File System Level: A New Approach to Secure Data in Shared Environment." International Journal of Computer Theory and Engineering 8, no. 3 (June 2016): 223–28. http://dx.doi.org/10.7763/ijcte.2016.v8.1048.
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Hong, Dong-Kweon. "Semantic Synchronization of Shared Data for Unstable Mobile Environment." Journal of Korean Institute of Intelligent Systems 25, no. 6 (December 25, 2015): 551–57. http://dx.doi.org/10.5391/jkiis.2015.25.6.551.
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TUIJNMAN, FRANK, and HAMIDEH AFSARMANESH. "MANAGEMENT OF SHARED DATA IN FEDERATED COOPERATIVE PEER ENVIRONMENT." International Journal of Cooperative Information Systems 02, no. 04 (December 1993): 451–73. http://dx.doi.org/10.1142/s0218215793000204.
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In a network of autonomous cooperating agents, complex distributed objects can be shared and exchanged. The novel feature presented in this paper is handling complex distributed objects, that we claim to be essential for cooperating teams of engineers e.g. in CIM, and in an environment that supports the integration of a group of expert systems. A model is presented here for the creation, retrieval, and modification of complex objects that are distributed in a federation of cooperating agents. The information that agents are willing to share with others in the federation is uniformly represented as inter-related objects. This defines a distributed object graph that spans over the entire federation of agents. Complex objects form a connected subgraph of this distributed object graph. To support safe cooperation and sharing of complex objects, while preserving agents’ autonomy, agents can bilaterally negotiate the access rights and deletion policies on distributed complex objects and when necessary these rights are propagated. Since the access rights are negotiated among agents, and not imposed by a central authority, the autonomy of each agent is fully maintained. To enable application programs to define and retrieve a complex object as a single entity, a linearization mechanism is introduced in the paper. The model described here has been developed as a part of the PEER system. PEER is a federated objectbase, designed and implemented as part of the Archon abstract machine, which provides an environment for the integration of heterogeneous cooperating expert systems.
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Obenson, Ken. "Ensuring integrity of forensic data in a shared practice environment." Forensic Science, Medicine, and Pathology 10, no. 2 (September 25, 2013): 284–85. http://dx.doi.org/10.1007/s12024-013-9486-7.
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Garg, Deepak, and Shalli Rani. "Dynamic Hybrid Secured Environment (DHSE) to Provide Confidentiality in Cloud Computing Environment." Journal of Computational and Theoretical Nanoscience 17, no. 6 (June 1, 2020): 2557–61. http://dx.doi.org/10.1166/jctn.2020.8930.
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With help of internet technology today people can process, store and share data easily moreover, cloud computing model has provided various application services to users such as storage because cloud provide pay as you go environment. Storage helps data owner to share their data among users or employees of organization. But there is a need for data owners to provide flexible access control such that unauthorized users cannot have access to the data and confidentiality can be maintained. In addition, there is a need that only encrypted data is shared over the cloud. Encryption schemes have a major role in security domain of cloud computing model. In this article, DHSE scheme which is a hybrid technique and uses AES, ABE and IBE for key and data encryption is proposed. Furthermore, to validate and to do the security investigation of our plan we have verified our results using AVISPA tools.
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Jasim, Omer K., Safia Abbas, El-Sayed M. El-Horbaty, and Abdel-Badeeh M. Salem. "Cryptographic Cloud Computing Environment as a More Trusted Communication Environment." International Journal of Grid and High Performance Computing 6, no. 2 (April 2014): 38–51. http://dx.doi.org/10.4018/ijghpc.2014040103.
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Cloud Communication Environment is an internet-based computing, where shared resources, software, and information are provided with computers and devices on-demand. They guarantee a way to share distributed resources and services that belong to different organizations. In order to develop cloud computing applications, security and trust to share data through distributed resources must be assured. This paper offers a study of the different mechanisms used in open cloud environments such as keys generation and management, and encryption/decryption algorithms. In addition, the paper proposes a new cryptographic environment, annotated as “CCCE” that deploys the combination between quantum key distribution mechanisms (QKD) and advanced encryption standard (AES), and demonstrates how quantum mechanics can be applied to improve computation.
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Lin, Jerry Chun-Wei, Jimmy Ming-Tai Wu, Philippe Fournier-Viger, Youcef Djenouri, Chun-Hao Chen, and Yuyu Zhang. "A Sanitization Approach to Secure Shared Data in an IoT Environment." IEEE Access 7 (2019): 25359–68. http://dx.doi.org/10.1109/access.2019.2899831.
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Pool, René, Fiona A. Hagenbeek, Anne M. Hendriks, Jenny van Dongen, Gonneke Willemsen, Eco de Geus, Ko Willems van Dijk, et al. "Genetics and Not Shared Environment Explains Familial Resemblance in Adult Metabolomics Data." Twin Research and Human Genetics 23, no. 3 (June 2020): 145–55. http://dx.doi.org/10.1017/thg.2020.53.
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AbstractMetabolites are small molecules involved in cellular metabolism where they act as reaction substrates or products. The term ‘metabolomics’ refers to the comprehensive study of these molecules. The concentrations of metabolites in biological tissues are under genetic control, but this is limited by environmental factors such as diet. In adult mono- and dizygotic twin pairs, we estimated the contribution of genetic and shared environmental influences on metabolite levels by structural equation modeling and tested whether the familial resemblance for metabolite levels is mainly explained by genetic or by environmental factors that are shared by family members. Metabolites were measured across three platforms: two based on proton nuclear magnetic resonance techniques and one employing mass spectrometry. These three platforms comprised 237 single metabolic traits of several chemical classes. For the three platforms, metabolites were assessed in 1407, 1037 and 1116 twin pairs, respectively. We carried out power calculations to establish what percentage of shared environmental variance could be detected given these sample sizes. Our study did not find evidence for a systematic contribution of shared environment, defined as the influence of growing up together in the same household, on metabolites assessed in adulthood. Significant heritability was observed for nearly all 237 metabolites; significant contribution of the shared environment was limited to 6 metabolites. The top quartile of the heritability distribution was populated by 5 of the 11 investigated chemical classes. In this quartile, metabolites of the class lipoprotein were significantly overrepresented, whereas metabolites of classes glycerophospholipids and glycerolipids were significantly underrepresented.
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Yang, Ying, Wenqin Cui, and Jinfang He. "An Empirical Analysis of the Correlation between Listed Companies’ Financial Shared Services and Corporate Innovation Performance: Based on the Empirical Data of A-Share Listed Companies." Mathematical Problems in Engineering 2022 (March 2, 2022): 1–7. http://dx.doi.org/10.1155/2022/8037582.
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With the rapid development of information technology, the financial sharing service is a new type of financial management that saves human capital, changes management concepts, improves management efficiency, and improves the internal control environment by centralizing the simple and repetitive work of enterprises. Financial shared services will strengthen the innovation capabilities of enterprises in terms of financial personnel, management personnel, and internal control environment. Therefore, in order to explore whether the new management model of financial shared services can bring about an improvement in the level of corporate innovation, this article starts from the perspective of financial shared services, takes A-share listed companies as the research sample, and uses the DID regression model to empirically analyze the relationship between financial shared services and the correlation between corporate innovation performance. The results of the research show that implementing financial sharing service can significantly improve enterprise innovation performance.
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Zagade, Pushkar, Shruti Yadav, Aishwarya Shah, and Ravindra Bachate. "Group User Revocation and Integrity Auditing of Shared Data in Cloud Environment." International Journal of Computer Applications 128, no. 12 (October 15, 2015): 22–25. http://dx.doi.org/10.5120/ijca2015906681.
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Brown, Dave F. "Experiencing Shared Leadership: Teachers’ Reflections." Journal of School Leadership 5, no. 4 (July 1995): 334–55. http://dx.doi.org/10.1177/105268469500500402.
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This eighteen month qualitative study documents an elementary school's implementation of a shared leadership environment. Data were collected from leadership team meetings, faculty meetings, informal interviews, and formal interviews with the leadership team. Findings indicate positive perceptions concerning collaboration and the development of an atmosphere of open communication. Respondents expressed disappointment with the level of decision-making opportunities, the development of non-student oriented goals, a lack of trust between administrators and teachers, and were confused about teacher roles and responsibilities. Shared leadership environments may be enhanced by providing clearer expectations for teachers and more opportunities for teacher training.
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Meakin, Brian, and Duncan Kemp. "5.7.3 Impact of Shared Data Environment - Enterprise Integration (SDE-EI) on Systems Engineering." INCOSE International Symposium 11, no. 1 (July 2001): 1121–27. http://dx.doi.org/10.1002/j.2334-5837.2001.tb02418.x.
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Zhang, Bing. "Unsupervised English Intelligent Machine Translation in Wireless Network Environment." Security and Communication Networks 2022 (May 21, 2022): 1–9. http://dx.doi.org/10.1155/2022/8208242.
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Researchers suggest unsupervised English machine translation to address the absence of parallel corpus in English translation. Unsupervised pretraining techniques, denoising autoencoders, back translation, and shared latent representation mechanisms are used to simulate the translation task using just monolingual corpora. This paper uses pseudo-parallel data to construct unsupervised neural machine translation (NMT) and dissimilar language pair analysis. This paper firstly analyzes the low performance of unsupervised translation on dissimilar language pairs from three aspects: bilingual word embedding quality, shared words, and word order. And artificial shared word replacement and preordering strategies are proposed to increase the shared words between dissimilar language pairs and reduce the difference in their syntactic structure, thereby improving the translation performance on dissimilar language pairs. The denoising autoencoder and shared latent representation mechanism in unsupervised English machine translation are only required in the early stage of training, and learning the shared latent representation limits the further improvement of performance in different directions. While training the denoising autoencoder by repeatedly altering the training data slows down the convergence of the model, this is especially true for divergent languages. This paper presents an unsupervised NMT model based on pseudo-parallel data to address this issue. It trains two standard supervised neural machine translation models using the pseudo-parallel corpus generated by the unsupervised neural machine translation system, which enhances translation performance and speeds convergence. Finally, the English intelligent translation model is deployed in the wireless network server, and users can access it through the wireless network.
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EVEN, SUSAN J., FRANS J. FAASE, and ROLF A. DE BY. "LANGUAGE FEATURES FOR COOPERATION IN AN OBJECT-ORIENTED DATABASE ENVIRONMENT." International Journal of Cooperative Information Systems 05, no. 04 (December 1996): 469–500. http://dx.doi.org/10.1142/s0218843096000178.
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We introduce the language LOTOS/TM for the formal specification of a network of cooperating agents with a shared data repository and private local data. LOTOS/TM is the orthogonal integration of the process-algebraic protocol specification language LOTOS and the functional, object-oriented database specification language TM. The specified world consists of a number of interacting LOTOS processes — describing the cooperating agents — and a special LOTOS process representing the shared data repository, which is modeled as a TM database. The data repository's functionality is made available to the other, cooperating processes through one or more external database gates. Interaction at such a gate corresponds to a method invocation in the database. In addition to shared persistent data, the TM language is used to specify the data encapsulated locally within processes, and the transient data communicated over gates. Some features of LOTOS/TM are inherently suitable for describing cooperation, such as combinators for synchronization on specific methods. These features are illustrated by examples showing navigation events on a shared graph structure that resembles a hypertext. Emphasis in the examples is placed on coordination aspects of the scenario. LOTOS/TM serves as a formalism for a more user-friendly specification language by the name of CoCoA that is currently under construction.
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Barchiesi, Daniele, Tobias Preis, Steven Bishop, and Helen Susannah Moat. "Modelling human mobility patterns using photographic data shared online." Royal Society Open Science 2, no. 8 (August 2015): 150046. http://dx.doi.org/10.1098/rsos.150046.
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Humans are inherently mobile creatures. The way we move around our environment has consequences for a wide range of problems, including the design of efficient transportation systems and the planning of urban areas. Here, we gather data about the position in space and time of about 16 000 individuals who uploaded geo-tagged images from locations within the UK to the Flickr photo-sharing website. Inspired by the theory of Lévy flights, which has previously been used to describe the statistical properties of human mobility, we design a machine learning algorithm to infer the probability of finding people in geographical locations and the probability of movement between pairs of locations. Our findings are in general agreement with official figures in the UK and on travel flows between pairs of major cities, suggesting that online data sources may be used to quantify and model large-scale human mobility patterns.
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Evtushenko, Sergej, and Iliya Puchenkov. "CREATING A BUILDING INFORMATION MODEL IN A SHARED DATA ENVI-RONMENT." Construction and Architecture 9, no. 1 (January 2, 2021): 46–50. http://dx.doi.org/10.29039/2308-0191-2021-9-1-46-50.
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The article presents the principles of joint work of subcontracting design organizations on the information model of the capital construction object. The organization of the general data environment developed by the general contractor is described. The tasks of the BIM manager, the optimal folder structure, and the levels of access to the information model of the participants in the design process are described.
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Wang, Harry, J. Leon Zhao, and Guoqing Chen. "Managing Data Security in E-Markets through Relationship Driven Access Control." Journal of Database Management 23, no. 2 (April 2012): 1–21. http://dx.doi.org/10.4018/jdm.2012040101.
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Data security in e-markets is vital to maintaining trust among trading partners. In an e-market, companies must share information to improve operational efficiency in their supply chains, while at the same time, access to sensitive information by rival companies should be prevented. In today’s highly dynamic business environment, the relationships among companies in e-markets are constantly changing while these relationships determine how company information should be shared with other companies. In this paper, the authors show that existing access control models are not designed for managing data security in e-markets with dynamic company relationships and propose a Relationship Driven Access Control (RDAC) model to provide a better solution. In particular, the authors design a rule-based approach for managing dynamic company relationships and a secure query processing mechanism to filter shared information based on company relationships. A prototype system is developed to demonstrate and validate the authors’ RDAC model.
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Rai, Rohit, and Upasna Singh. "Survey on User Group Revocation and Integrity Auditing of Shared Data in Cloud Environment." International Journal of Computer Sciences and Engineering 6, no. 12 (December 31, 2018): 481–87. http://dx.doi.org/10.26438/ijcse/v6i12.481487.
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Chang, Jyh-Biau, Po-Cheng Chen, Ce-Kuen Shieh, Jia-Hao Yang, and Sheng-Hung Hsieh. "An Adaptive-Grained Consistency Maintenance Scheme for Shared Data on Emergency and Rescue Applications." International Journal of Grid and High Performance Computing 5, no. 2 (April 2013): 54–71. http://dx.doi.org/10.4018/jghpc.2013040104.
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Efficient information sharing is difficult to achieve in the scenario of emergency and rescue operations because there is no communication infrastructure at the disaster sites. In general, the network condition is relatively reliable in the intra-site environment but relatively unreliable in the inter-site environment. The network partitioning problem may occur between two sites. Although one can exploit the replication technique used in data grid to improve the information availability in emergency and rescue applications, the data consistency problem occurs between replicas. In this paper, the authors propose a middleware called “Seagull” to transparently manage the data availability and consistency issues of emergency and rescue applications. Seagull adopts the optimistic replication scheme to provide the higher data availability in the inter-site environment. It also adopts the pessimistic replication scheme to provide the stronger data consistency guarantee in the intra-site environment. Moreover, it adopts an adaptive consistency granularity strategy that achieves the better performance of the consistency management because this strategy provides the higher parallelism when the false sharing happens. Lastly, Seagull adopts the transparency data consistency management scheme, and thus the users do not need to modify their source codes to run on the Seagull.
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Lamrini, Loubna, Mohammed Chaouki Abounaima, Fatima Zahra El Mazouri, Mohammed Ouzarf, and Mohammed TALIBI ALAOUI. "MCDM Filter with Pareto Parallel Implementation in Shared Memory Environment." Statistics, Optimization & Information Computing 10, no. 1 (February 8, 2022): 192–203. http://dx.doi.org/10.19139/soic-2310-5070-1216.
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Nowadays, multi-criteria decision-making (MCDM) methods are often used to solve problems involving large data sets, especially with the advent of the big data age. In such a context, the multi-criteria decision-making methods theoretically can be used but technically are not effificient in terms of the treatment time. Indeed, the majority of commercial or even experimental multi-criteria decision support tools always have limits in terms of the number of alternatives and the number of criteria to be retained in the decision-making process, which presents a computational challenge to relieve. This present paper discusses the application of parallel computation to meet this challenge and make the application of MCDM methods possible in the presence of a big number of alternatives and criteria. More precisely, the main objective of this work is to provide a parallel fifiltering mechanism that can be executed even on accessible personal computers and offering a short and reasonable response time. The introduction of a fifilter as a fifirst step in the decision-making process consists in retaining, as alternatives to be treated by the MCDM method, and by parallel processing only the Pareto solutions. To achieve this objective, we propose a parallel computing approach deploying the Open MP (Open Multi-Processing) paradigm on a shared memory environment to fifind Pareto solutions. To prove the effectiveness of the proposed approach for problems with large dimensionality, several numerical examples with different dimensions will be examined.
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Yan, Yun Xue, Lei Wu, Wen Yu Xu, Hao Wang, and Zhao Man Liu. "Integrity Audit of Shared Cloud Data with Identity Tracking." Security and Communication Networks 2019 (March 6, 2019): 1–11. http://dx.doi.org/10.1155/2019/1354346.
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More and more users are uploading their data to the cloud without storing any copies locally. Under the premise that cloud users cannot fully trust cloud service providers, how to ensure the integrity of users’ shared data in the cloud storage environment is one of the current research hotspots. In this paper, we propose a secure and effective data sharing scheme for dynamic user groups. (1) In order to realize the user identity tracking and the addition and deletion of dynamic group users, we add a new role called Rights Distribution Center (RDC) in our scheme. (2) To protect the privacy of user identity, when performing third party audit to verify data integrity, it is not possible to determine which user is a specific user. Therefore, the fairness of the audit can be promoted. (3) Define a new integrity audit model for shared cloud data. In this scheme, the user sends the encrypted data to the cloud and the data tag to the Rights Distribution Center (RDC) by using data blindness technology. Finally, we prove the security of the scheme through provable security theory. In addition, the experimental data shows that our proposed scheme is more efficient and scalable than the state-of-the-art solution.
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Palantzas, Georgios, and Dimitrios Nalmpantis. "Data and perspectives on e-scooters use in Greece." Ekistics and the new habitat 81, no. 1 (February 1, 2022): 28–36. http://dx.doi.org/10.53910/26531313-e2021811503.
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The issue of micromobility has been raised suddenly in recent years and although it includes several transportation modes, in shared or private form, shared e-scooters have become the fastest growing trend. While private e-scooters have been on the market for decades, the phenomenon of the shared e-scooter systems emerged mainly due to the advances of innovative technologies. However, the main question today is how e-scooters could be integrated into the urban environment of cities in terms of environmental, economic, and social performance, especially towards providing better first/last/only-mile connectivity. The answer is not simple because their sustainability in relation to the mobility system is mainly determined by how they are used and what they replace. If an e-scooter trip replaces a motorcycle or a car trip, the environmental and health effects are positive. If it replaces a trip on foot or by bike, the situation gets worse. This paper gives an overview of e-scooters’ use in Mediterranean cities, presents some preliminary results of a relevant ongoing quantitative survey in Greece, and offers a discussion on available data, challenges, and perspectives. The rides of shared e-scooters in several Mediterranean cities have overcome the one (1) million in just 10-12 months after their availability, while private e-scooter market shows also a growing demand. Given that this new mode of transport is still in its infancy, in this paper we examine the first indications in regard to its necessity, attractiveness, safety, cost, people’s attitudes, and integration into the urban environment focusing on Mediterranean cities.
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Inbaraj, X. Alphonse, and A. Seshagiri Rao. "Modified Secure Data Deduplication Computing in Cloud based Environment." Circulation in Computer Science 2, no. 7 (August 20, 2017): 14–19. http://dx.doi.org/10.22632/ccs-2017-252-42.
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Security has been a concern since the early days of computing, when a computer was isolated in a room and a threat could be posed only by malicious insiders. To support authorized Data Deduplication in cloud computing ,encryption is enhanced before outsource. Data Deduplication helps to store identical copy of data in Cloud Storage and that consumption is low bandwidth. Third Party control generates a spectrum of concerns caused by the lack of transparency and limited user control .For example , a cloud provider may subcontract some resources from a third party whose level of trust is questionable. There are examples when subcontractors fails to maintain the customer data. There are also examples when third party was not a subcontractor but a hardware supplier and the loss of data was caused by poor –quality storage devices[12].To overcome the problem of integrity and security, this paper makes the first attempt that applying Data Coloring, Watermarking techniques on shared data objects. Then applying Merkle Hash Tree[11],make tighten access control for sensitive data in both private and public clouds.
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Chen, Yanqing. "Enterprise Financial Data Sharing Based on Information Fusion Cloud Computing Environment." Wireless Communications and Mobile Computing 2022 (January 15, 2022): 1–11. http://dx.doi.org/10.1155/2022/5994628.
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At present, many companies have many problems such as high financial costs, low financial management capabilities, and redundant frameworks; at the same time, the SASAC requires that the enterprise’s financial strategy transfer from “profit-driven” to “value-driven”, finance separate from accounting to improve the operational efficiency of the company. Under this background, more and more enterprise respond to the call of the SASAC; in order to achieve the goals of corporate financial cost savings and financial management efficiency improved, we began to provide services through financial sharing. The research of information fusion theory involves many basic theories, which can be roughly divided into two large categories from the algorithmic point of view: probabilistic statistical method and artificial intelligence method. The main task of artificial intelligence is to realize the computer for some learning, thinking process, and wisdom formation of simulation, and an important goal of information integration is the human brain comprehensive processing ability simulation, so artificial intelligence method will have broad application prospects in the field of information fusion; the common methods have D-S evidence reasoning, fuzzy theory, neural network, genetic algorithm, rough set, and other information fusion methods. The purpose of this paper is to proceed from the internal financial situation of the enterprise, analyze data security issues in the operation of financial shared services, and find a breakthrough in solving problems. But, with constantly expanding of enterprise group financial sharing service scale, the urgent problem to be solved is how to ensure the financial sharing services provided by enterprises in the cloud computing environment. This paper combines financial sharing service theory and information security theory and provides reference for building financial sharing information security for similar enterprises. For some enterprise that have not established a financial shared service center yet, they can learn from the establishment of the financial sharing information security system in this paper and provide a reference for enterprise to avoid the same types of risks and problems. For enterprise that has established and has begun to practice a financial shared information security system, appropriate risk aversion measures combined with actual situation of the enterprise with four dimensions related to information security system optimization was formulated and described in this paper. In summary, in the background of cloud computing, financial sharing services have highly simplified operational applications, and data storage capabilities and computational analysis capabilities have been improved greatly. Not only can it improve the quality of accounting information but also provide technical support for the financial sharing service center of the enterprise group, perform financial functions better, and enhance decision support and strategic driving force, with dual practical significance and theoretical significance.
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Petersen, Carolyn, Margo Edmunds, Deven McGraw, Elisa L. Priest, Jeffery R. L. Smith, Eagan Kemp, and Hugo Campos. "A Policy Framework to Support Shared Decision-Making through the Use of Person-Generated Health Data." ACI Open 05, no. 02 (July 2021): e104-e115. http://dx.doi.org/10.1055/s-0041-1736632.
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Abstract Background Individuals increasingly want to access, contribute to, and share their personal health information to improve outcomes, such as through shared decision-making (SDM) with their care teams. Health systems' growing capacity to use person-generated health data (PGHD) expands the opportunities for SDM. However, SDM not only lacks organizational and information infrastructure support but also is actively undermined, despite public interest in it. Objectives This work sought to identify challenges to individual–clinician SDM and policy changes needed to mitigate barriers to SDM. Methods Two multi-stakeholder group of consumers, patients, caregivers; health services researchers; and experts in health policy, informatics, social media, and user experience used a consensus process based on Bardach's policy analysis framework to identify barriers to SDM and develop recommendations to reduce these barriers. Results Technical, legal, organizational, cultural, and logistical obstacles make data sharing difficult, thereby undermining use of PGHD and realization of SDM. Stronger privacy, security, and ethical protections, including informed consent; promoting better consumer access to their data; and easier donation of personal data for research are the most crucial policy changes needed to facilitate an environment that supports SDM. Conclusion Data protection policy lags far behind the technical capacity for third parties to share and reuse electronic information without appropriate permissions, while individuals' right to access their own health information is often restricted unnecessarily, poorly understood, and poorly communicated. Sharing of personal information in a private, secure environment in which data are shared only with individuals' knowledge and consent can be achieved through policy changes.
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Yang, Jin Cai, Qi Chen, Zhong Hua Wang, and Jin Zhu Hu. "Data Allocation Strategy Based on Users Moving in a Mobile Computing Environment." Advanced Engineering Forum 6-7 (September 2012): 404–9. http://dx.doi.org/10.4028/www.scientific.net/aef.6-7.404.
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Mobile users tend to submit transactions to servers nearby for execution so as to minimize the communication overhead incurred. Data replication is helpful because it can improve execution performance of servers and reduce network traffic. In this paper, a new algorithm named SDMP (shared data allocation algorithm based on moving pattern) is proposed, which takes not only the user’s pattern but also the frequency of user’s appearance according to the user’s path log into account. Experimental results show the SDMP algorithm is better than other algorithms used for data allocation for servers.
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Torgersen, Anne Mari, and Harald Janson. "Why do Identical Twins Differ in Personality: Shared Environment Reconsidered." Twin Research 5, no. 1 (February 1, 2002): 44–52. http://dx.doi.org/10.1375/twin.5.1.44.
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AbstractWhile heritability studies show that most of the variance in adult personality can be attributed to genetic or so-called nonshared environmental influence, this does not mean that shared events lack importance for the development of later personality differences. We studied the relationship between Big Five personality differences in monozygotic (MZ) twins at age 29, and life stressors at age 6 to 15, using prospective data from 26 MZ pairs studied from birth onwards. A positive significant correlation was found between stressors in childhood and early adolescence, and intrapair personality differences in Agreeableness, Openness, Conscientiousness, and five-factor profiles. We note that the effects of shared events are labeled “nonshared” environment when the effect is to make siblings more different. Case examples illustrate the relationship between stress and personality differences, and provide hypotheses for further studies in larger samples.
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Bauman, David, Jason Vleminckx, Olivier J. Hardy, and Thomas Drouet. "Testing and interpreting the shared space-environment fraction in variation partitioning analyses of ecological data." Oikos 128, no. 2 (October 30, 2018): 274–85. http://dx.doi.org/10.1111/oik.05496.
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ELEY, THALIA C., PAUL LICHTENSTEIN, and TERRIE E. MOFFITT. "A longitudinal behavioral genetic analysis of the etiology of aggressive and nonaggressive antisocial behavior." Development and Psychopathology 15, no. 2 (June 2003): 383–402. http://dx.doi.org/10.1017/s095457940300021x.
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Developmental studies of antisocial behavior (ASB) have found two subgroups of behaviors, roughly described as aggressive and nonaggressive ASB. Theoretical accounts predict that aggressive ASB, which shows greater stability, should have high heritability. In contrast, nonaggressive ASB is very common in adolescence, shows less continuity, and should be influenced both by genes and shared environment. This study explored the genetic and environmental influences on aggressive and nonaggressive ASB in over 1,000 twin pairs aged 8–9 years and again at 13–14 years. Threshold models were fit to the data to incorporate the skew. In childhood, aggressive ASB was highly heritable and showed little influence of shared environment, whereas nonaggressive ASB was significantly influenced both by genes and shared environment. In adolescence, both variables were influenced both by genes and shared environment. The continuity in aggressive antisocial behavior symptoms from childhood to adolescence was largely mediated by genetic influences, whereas continuity in nonaggressive antisocial behavior was mediated both by the shared environment and genetic influences. These data are in agreement with the hypothesis that aggressive ASB is a stable heritable trait as compared to nonaggressive behavior, which is more strongly influenced by the environment and shows less genetic stability over time.
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Tsai, Chwei-Shyong, Hsin-Liang Chen, Hsien-Chu Wu, and Josh Jia-Ching Ying. "A Puzzle-Based Data Sharing Approach with Cheating Prevention Using QR Code." Symmetry 13, no. 10 (October 8, 2021): 1896. http://dx.doi.org/10.3390/sym13101896.
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The information technique has developed rapidly. The technique of QR codes is widely applied in our daily life, and the mechanism is suitable to share data. A QR code uses symmetric encryption to store and retrieve data efficiently. However, the security issues of QR codes are seldom discussed by the wider community. Moreover, if the sender wishes only the authorized participant to attain the private data which are shared, the data must be encrypted. Furthermore, we do not know who should be censured when problems arise. In view of this, to maintain the integrity and the confidentiality of information security, this paper proposed a new puzzle-based data sharing scheme to share the private information safely. Firstly, we generated the digital signature of the information, then applied the random grids algorithm to obtain the shares. Then, we disarrayed the shares which contain the information and the digital signature with a puzzle-based encoding method. Afterwards, we concealed them into the cover QR codes. With the QR code mechanism of error correction, the marked QR code remain meaningful. Finally, we could send marked QR codes via transmission. The receiver could use XOR operation to obtain the private information after solving the puzzles and verify whether it was tampered with by the digital signature. The proposed system can recover the lossless data and protect them from being divulged. To deal with the potential hazard of transmission in a public environment, there are more and more studies on data hiding and image authentication.
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Valra, Alessandro, Davide Madeddu, Jacopo Chiappetti, and Diego Farina. "The BIM Management System: A Common Data Environment Using Linked Data to Support the Efficient Renovation in Buildings." Proceedings 65, no. 1 (January 1, 2021): 18. http://dx.doi.org/10.3390/proceedings2020065018.
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One of the main challenges of the construction industry is the management of the huge amount of data generated by the stakeholders during the whole lifecycle of the buildings. Data needs to be found, collected, shared, and updated minimizing the process and technological inefficiencies. Recent advances have been seen in the adoption of BIM-based approaches and in the implementation of CDE as an agreed source of information. This paper describes the development of the BIM management system as a platform to manage the building lifecycle data using the linked data paradigm to improve the interoperability and the interdisciplinary collaboration
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Reeve, Carlton. "Presence in Virtual Theater." Presence: Teleoperators and Virtual Environments 9, no. 2 (April 2000): 209–13. http://dx.doi.org/10.1162/105474600566727.
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Using empirical data, this research suggests that key features of a typical theatrical rehearsal process can significantly improve the sense of presence for participants within a shared virtual environment. Research of shared virtual environments (VEs) for the production of theater shows suggests that theater applications have specific requirements for presence. These can be summarized as characterization, repetition, and group dynamic, while the level of presence is dependent on the actor-avatar, actor-space, and actor-actor relationships.
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BUSTER, MAURY A., and JOSEPH LEE RODGERS. "GENETIC AND ENVIRONMENTAL INFLUENCES ON ALCOHOL USE: DF ANALYSIS OF NLSY KINSHIP DATA." Journal of Biosocial Science 32, no. 2 (April 2000): 177–89. http://dx.doi.org/10.1017/s0021932000001772.
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Research designs to study alcohol use and abuse have included twin, adoption and family history/high risk studies. Results have consistently implied a genetic factor in the aetiology of alcohol abuse. However, less research has been conducted in search of environmental factors. This study uses kinship structure in a large national dataset (the National Longitudinal Survey of Youth) to estimate (using DeFries–Fulker analysis) the extent of the shared genetic, non-shared genetic, shared environmental and non-shared environmental influences on alcohol use. The NLSY kinship sample contained 3890 pairs of cousins, half-siblings, full-siblings and twins between the ages of 14 and 21 in the initial year of the survey (1979). Estimates of heritability (h2) and shared environment (c2) were small to moderate for the entire dataset for both light drinking and heavy drinking behaviour, with h2 estimates slightly higher in each case. Non-shared genetic measures of self-esteem and locus of control accounted for a significant portion of the remaining variance in heavy drinking behaviour. Race and gender patterns showed c2 and h2 estimates that were also small to moderate for both light and heavy drinking behaviour. Significant non-shared effects were found for the White group for heavy drinking behaviour, and for male pairs for both heavy and light drinking behaviour. Additionally, implications and future directions are discussed.
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Qi, Hui Ying, and Jian Guang Guo. "A Biorepository Management Scheme for Data Integration." Applied Mechanics and Materials 411-414 (September 2013): 353–56. http://dx.doi.org/10.4028/www.scientific.net/amm.411-414.353.
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The multiple-institutions-based collaborated researchers securely exchange information and data sharing to gain insight into complex, variable diseases from many different types of information in various institutions. A novel approach to biorepository management scheme for information integration is presented. It integrates a large number of data types through a unified standardization. Local biorepository is the largest collection of local data. Central biorepository that integrates of all the local biorepository information can be shared and is the largest available collection of shared information resources. The key point between central biorepository and local biorepository is in two ways: The integration of local biorepository data; local biorepository queries and downloads the data from the database system. This method realizes a good harvesting feature from local biorepository to central biorepository; local biorepository can also access database system to obtain data sharing in a distributed environment.
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Yang, Fan, Fan Ding, Xu Qu, and Bin Ran. "Estimating Urban Shared-Bike Trips with Location-Based Social Networking Data." Sustainability 11, no. 11 (June 11, 2019): 3220. http://dx.doi.org/10.3390/su11113220.
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Dockless shared-bikes have become a new transportation mode in major urban cities in China. Excessive number of shared-bikes can occupy a significant amount of roadway surface and cause trouble for pedestrians and auto vehicle drivers. Understanding the trip pattern of shared-bikes is essential in estimating the reasonable size of shared-bike fleet. This paper proposed a methodology to estimate the shared-bike trip using location-based social network data and conducted a case study in Nanjing, China. The ordinary least square, geographically weighted regression (GWR) and semiparametric geographically weighted regression (SGWR) methods are used to establish the relationship among shared-bike trip, distance to the subway station and check ins in different categories of the point of interest (POI). This method could be applied to determine the reasonable number of shared-bikes to be launched in new places and economically benefit in shared-bike management.
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Jin, Hee-Jeong, Jeong-Won Lee, and Hwan-Gue Cho. "A Reliable and Distributed LIMS for Efficient Management of the Microarray Experiment Environment." Journal of Integrative Bioinformatics 4, no. 1 (March 1, 2007): 115–31. http://dx.doi.org/10.1515/jib-2007-57.
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Summary A microarray is a principal technology in molecular biology. It generates thousands of expressions of genotypes at once. Typically, a microarray experiment contains many kinds of information, such as gene names, sequences, expression profiles, scanned images, and annotation. So, the organization and analysis of vast amounts of data are required. Microarray LIMS (Laboratory Information Management System) provides data management, search, and basic analysis. Recently, microarray joint researches, such as the skeletal system disease and anti-cancer medicine have been widely conducted. This research requires data sharing among laboratories within the joint research group. In this paper, we introduce a web based microarray LIMS, SMILE (Small and solid MIcroarray Lims for Experimenters), especially for shared data management. The data sharing function of SMILE is based on Friend-to-Friend (F2F), which is based on anonymous P2P (Peer-to-Peer), in which people connect directly with their “friends”. It only allows its friends to exchange data directly using IP addresses or digital signatures you trust. In SMILE, there are two types of friends: “service provider”, which provides data, and “client”, which is provided with data. So, the service provider provides shared data only to its clients. SMILE provides useful functions for microarray experiments, such as variant data management, image analysis, normalization, system management, project schedule management, and shared data management. Moreover, it connections with two systems: ArrayMall for analyzing microarray images and GENAW for constructing a genetic network. SMILE is available on http://neobio.cs.pusan.ac.kr:8080/smile.
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Zotov, Vladimir, Iman Ibrahim, Irina Petunina, and Yuliya Lazareva. "Engagement of Students in Data Visualization for the Purpose of E-Learning Improvement." International Journal of Emerging Technologies in Learning (iJET) 16, no. 02 (January 26, 2021): 46. http://dx.doi.org/10.3991/ijet.v16i02.18745.
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The study describes an approach to e-learning based on the Moodle platform that is used to visualize participation in the learning community and is proposed to be used to inform students and teachers about their involvement in the social learn-ing environment. The experiment involved 5 teachers and 3 experts who deter-mined the most significant visualization indicators for the virtual learning envi-ronment dashboards. There were 42 students aged 21 to 23. The virtual learning environment is based on the Moodle and Blackboard platforms that are common-ly used in universities. SocialWall allowed participants to perform actions in the social environment that are visualized in graphs under the specified criteria. A Wiki repository plugin was also added in order to accumulate student knowledge in shared structured documents stored in a shared repository. The relational data-base management system MySQL allows creation of additional relations, data-base design and administration. The visualization activities described in the study are based on modified state transition networks to analyze and visualize the stu-dent learning path. Student trajectory networks show the interaction of individual learners or groups with the course structure and material.
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Wang, Pan, and Ian Bishop. "Real-Time Data Visualisation in Collaborative Virtual Environment for Emergency Management." International Journal of Information Systems for Crisis Response and Management 5, no. 4 (October 2013): 13–44. http://dx.doi.org/10.4018/ijiscram.2013100102.
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A collaborative virtual environment (CVE) is a shared virtual environment used for collaboration of many participants that may be spread over large distances. CVEs have been widely used in emergency management, especially for education, training and assessment. This paper describes the design and implementation of a prototype system that facilitates emergency management via a CVE using real-time spatial information. In particular, a method for automatic integration, modeling and visual simulation using real-time data from multiple online sources is proposed. Moreover, strategies are presented for using CVE-based scenarios for carrying out training, and testing preparedness measures. A novel technique has also been developed for real-time situation monitoring. Based on a system development (SD) research approach, the performance and functionality of the system was tested and evaluated. The use of real-time data acquisition and simulation was deemed to improve the processes of emergency management by increasing engagement, enhancing training and supporting decision-making of first responders and emergency managers.
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Peng, Rui, Kien A. Hua, Hao Cheng, and Fei Xie. "An Internet Framework for Pervasive Sensor Computing." International Journal of Advanced Pervasive and Ubiquitous Computing 1, no. 3 (July 2009): 1–22. http://dx.doi.org/10.4018/japuc.2009090801.
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The rapid increase of sensor networks has brought a revolution in pervasive computing. However, data from these fragmented and heterogeneous sensor networks are easily shared. Existing sensor computing environments are based on the traditional database approach, in which sensors are tightly coupled with specific applications. Such static configurations are effective only in situations where all the participating sources are precisely known to the application developers, and users are aware of the applications. A pervasive computing environment raises more challenges, due to ad hoc user requests and the vast number of available sources, making static integration less effective. This paper presents an Internet framework called iSEE (Internet Sensor Exploration Environment) which provides a more complete environment for pervasive sensor computing. iSEE enables advertising and sharing of sensors and applications on the Internet with unsolicited users much like how Web pages are publicly shared today.
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Huang, Weihua. "Research on the Revolution of Multidimensional Learning Space in the Big Data Environment." Complexity 2021 (May 18, 2021): 1–12. http://dx.doi.org/10.1155/2021/6583491.
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Multiuser fair sharing of clusters is a classic problem in cluster construction. However, the cluster computing system for hybrid big data applications has the characteristics of heterogeneous requirements, which makes more and more cluster resource managers support fine-grained multidimensional learning resource management. In this context, it is oriented to multiusers of multidimensional learning resources. Shared clusters have become a new topic. A single consideration of a fair-shared cluster will result in a huge waste of resources in the context of discrete and dynamic resource allocation. Fairness and efficiency of cluster resource sharing for multidimensional learning resources are equally important. This paper studies big data processing technology and representative systems and analyzes multidimensional analysis and performance optimization technology. This article discusses the importance of discrete multidimensional learning resource allocation optimization in dynamic scenarios. At the same time, in view of the fact that most of the resources of the big data application cluster system are supplied to large jobs that account for a small proportion of job submissions, while the small jobs that account for a large proportion only use the characteristics of a small part of the system’s resources, the expected residual multidimensionality of large-scale work is proposed. The server with the least learning resources is allocated first, and only fair strategies are considered for small assignments. The topic index is distributed and stored on the system to realize the parallel processing of search to improve the efficiency of search processing. The effectiveness of RDIBT is verified through experimental simulation. The results show that RDIBT has higher performance than LSII index technology in index creation speed and search response speed. In addition, RDIBT can also ensure the scalability of the index system.
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Testi, Debora, Paolo Quadrani, and Marco Viceconti. "PhysiomeSpace: digital library service for biomedical data." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 368, no. 1921 (June 28, 2010): 2853–61. http://dx.doi.org/10.1098/rsta.2010.0023.
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Every research laboratory has a wealth of biomedical data locked up, which, if shared with other experts, could dramatically improve biomedical and healthcare research. With the PhysiomeSpace service, it is now possible with a few clicks to share with selected users biomedical data in an easy, controlled and safe way. The digital library service is managed using a client–server approach. The client application is used to import, fuse and enrich the data information according to the PhysiomeSpace resource ontology and upload/download the data to the library. The server services are hosted on the Biomed Town community portal, where through a web interface, the user can complete the metadata curation and share and/or publish the data resources. A search service capitalizes on the domain ontology and on the enrichment of metadata for each resource, providing a powerful discovery environment. Once the users have found the data resources they are interested in, they can add them to their basket, following a metaphor popular in e-commerce web sites. When all the necessary resources have been selected, the user can download the basket contents into the client application. The digital library service is now in beta and open to the biomedical research community.
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Denker, A. "PROTECTION OF PRIVACY AND PERSONAL DATA IN THE BIG DATA ENVIRONMENT OF SMART CITIES." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVI-4/W5-2021 (December 23, 2021): 181–86. http://dx.doi.org/10.5194/isprs-archives-xlvi-4-w5-2021-181-2021.
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Abstract. The project of smart cities has emerged as a response to the challenges of twenty-first- century urbanization. Solutions to the fundamental conundrum of cities revolving around efficiency, convenience and security keep being sought by leveraging technology. Notwithstanding all the conveniences furnished by a smart city to all the citizens, privacy of a citizen is intertwined with the benefits of a smart city. The development processes which overlook privacy and security issues have left many of the smart city applications vulnerable to non-conventional security threats and susceptible to numerous privacy and personal data spillage risks. Among the challenges the smart city initiatives encounter, the emergence of the smartphone-big data-the cloud coalescence is perhaps the greatest, from the viewpoint of privacy and personal data protection. As our cities are getting digitalized, information comprising citizens' behavior, choices, and mobility, as well as their personal assets are shared over smartphone-big data-the cloud coalescences, thereby expanding cyber-threat surface and creating different security concerns. This coalescence refers to the practices of creating and analyzing vast sets of data, which comprise personal information. In this paper, the protection of privacy and personal data issues in the big data environment of smart cities are viewed through bifocal lenses, focusing on social and technical aspects. The protection of personal data and privacy in smart city enterprises is treated as a socio-technological operation where various actors and factors undertake different tasks. The article concludes by calling for novel developments, conceptual and practical changes both in technological and social realms.
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Whitfield, John B., Gu Zhu, Andrew C. Heath, and Nicholas G. Martin. "Choice of Residential Location: Chance, Family Influences, or Genes?" Twin Research and Human Genetics 8, no. 1 (February 1, 2005): 22–26. http://dx.doi.org/10.1375/twin.8.1.22.
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AbstractThe choice of where to live would appear to be determined by a combination of economic constraints and personal preferences. We have tested how far this choice is affected by the continuing effects of the environment shared within families, and genetic variation between people, using data from twin studies conducted in Australia. The addresses provided by study participants were categorized as urban, suburban and nonurban, and data were analyzed in three adult age groups. There were significant effects of both shared environment and genes, and the balance between them was affected by both sex and age. Shared environment accounted for some 50% of variation in the youngest group, but only about 10% in the oldest. As shared environmental effects decreased, additive genetic effects increased. These results have implications for internal migration of people within countries and, over the long term, for gene flow within and between populations. They may also be pertinent to the different prevalences of certain psychiatric diseases between city and country locations. Comparisons between countries with different demography are needed to confirm and further characterize these effects.
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Bares, Cristina B., Hermine H. Maes, and Kenneth S. Kendler. "Familial and Special Twin Influences on Cigarette Use Initiation." Twin Research and Human Genetics 20, no. 2 (March 17, 2017): 137–46. http://dx.doi.org/10.1017/thg.2017.10.
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Background: Shared experiences within families play an important role in the initiation of cigarette use among adolescents. Behavioral genetic studies using various samples have implicated that the shared environment that twins experience is an important source of influence on whether adolescents initiate cigarette use. Whether the special twin environment, in addition to the shared environment, contributes significantly to making twin siblings more similar in cigarette initiation, and whether the influence of the special twin environment persists into adulthood, is less clear. Methods: Data for this study came from the National Longitudinal Survey of Adolescent Health. Twin, full-, and half-sibling pairs between the ages of 12 and 33 were separated into three age groups, with about 3,000 individuals in each age group. The proportion of variance in cigarette use initiation explained by genetic, shared, special twin, and unique environmental factors were examined. Results: The results of separate age-moderated univariate variance decomposition models indicate that the special twin environment does not significantly contribute to the variance in cigarette use initiation in adolescence or young adulthood. Conclusion: Factors shared by individuals in a family, but that are not specific to being a twin, are important in determining whether adolescents will initiate the use of cigarettes.
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Atazadeh, Behnam, Hamed Olfat, Behzad Rismanchi, Davood Shojaei, and Abbas Rajabifard. "Utilizing a Building Information Modelling Environment to Communicate the Legal Ownership of Internet of Things-Generated Data in Multi-Owned Buildings." Electronics 8, no. 11 (November 1, 2019): 1258. http://dx.doi.org/10.3390/electronics8111258.
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In multi-owned buildings, a community of residents live in their private properties while they use and share communal spaces and facilities. Proper management of multi-owned buildings is underpinned by rules related to health, safety, and security of the residents and visitors. Utilizing Internet of Things (IoT) devices to collect information about the livable space has become a significant trend since the introduction of first smart home appliances back in 2000. The question about who owns the IoT generated data and under what terms it can be shared with others is still unclear. IoT devices, such as security camera and occupancy sensors, can provide safety for their owners, while these devices may capture private data from the neighborhood. In fact, the residents are sometimes not aware of regulations that can prevent them from installing and collecting data from shared spaces that could breach other individuals’ privacy. On the other hand, Building Information Modelling (BIM) provides a rich 3D digital data environment to manage the physical, functional, and ownership aspects of buildings over their entire lifecycle. This study aims to propose a methodology to utilize BIM for defining the legal ownership of the IoT generated data. A case study has been used to discuss key challenges related to the ownership of IoT data in a multi-owned building. This study confirmed that BIM environment can facilitate the understanding of legal ownership of IoT datasets and supports the interpretation of who has the entitlement to use the IoT datasets in multi-owned buildings.
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Paris, Bonnie L., and Denise M. Hynes. "Diffusion, implementation, and use of Research Electronic Data Capture (REDCap) in the Veterans Health Administration (VA)." JAMIA Open 2, no. 3 (June 11, 2019): 312–16. http://dx.doi.org/10.1093/jamiaopen/ooz017.
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Abstract This case study describes the implementation of the Research Electronic Data Capture (REDCap) software at the United States Department of Veterans Affairs Veterans Health Administration (VA). VA REDCap enables secure and standardized data collection, fosters collaboration with external researchers through use of a widely used data management tool, facilitates multisite studies through use of data forms that can be shared across sites within and outside the VA, is well suited to health services research studies and quality improvement projects, and enables exporting data for analysis in the VA secure computing environment. Using a diffusion of innovation framework approach, authors explore organizational factors that shaped adoption of REDCap technology and constraints on its use within the VA. Lessons learned from the VA experience are discussed.
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Schuwerk, Clemens, Giulia Paggetti, Rahul Chaudhari, and Eckehard Steinbach. "Perception-Based Traffic Control for Shared Haptic Virtual Environments." Presence: Teleoperators and Virtual Environments 23, no. 3 (October 1, 2014): 320–38. http://dx.doi.org/10.1162/pres_a_00196.
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Shared Haptic Virtual Environments (SHVEs) are often realized using a client–server communication architecture. In this case, a centralized physics engine, running on the server, is used to simulate the object-states in the virtual environment (VE). At the clients, a copy of the VE is maintained and used to render the interaction forces locally, which are then displayed to the human through a haptic device. While this architecture ensures stability in the coupling between the haptic device and the virtual environment, it necessitates a high number of object-state update packets transmitted from the server to the clients to achieve satisfactory force feedback quality. In this paper, we propose a perception-based traffic control scheme to reduce the number of object-state update packets by allowing a variable but not perceivable object-state error at the client. To find a balance between packet rate reduction and force rendering fidelity, our approach uses different error thresholds for the visual and haptic modality, where the haptic thresholds are determined by psychophysical experiments in this paper. Force feedback quality is evaluated with subjective tests for a variety of different traffic control parameter settings. The results show that the proposed scheme reduces the packet rate by up to 97%, compared to communication approaches that work without data reduction. At the same time, the proposed scheme does not degrade the haptic feedback quality significantly. Finally, it outperforms well-known dead reckoning, commonly used in visual-only distributed applications.
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Gomez-Diaz, Teresa, and Tomas Recio. "Research Software vs. Research Data I: Towards a Research Data definition in the Open Science context." F1000Research 11 (January 28, 2022): 118. http://dx.doi.org/10.12688/f1000research.78195.1.
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Background: Research Software is a concept that has been only recently clarified. In this paper we address the need for a similar enlightenment concerning the Research Data concept. Methods: Our contribution begins by reviewing the Research Software definition, which includes the analysis of software as a legal concept, followed by the study of its production in the research environment and within the Open Science framework. Then we explore the challenges of a data definition and some of the Research Data definitions proposed in the literature. Results: We propose a Research Data concept featuring three characteristics: the data should be produced (collected, processed, analyzed, shared & disseminated) to answer a scientific question, by a scientific team, and has yield a result published or disseminated in some article or scientific contribution of any kind. Conclusions: The analysis of this definition and the context in which it is proposed provides some answers to the Borgman’s conundrum challenges, that is, which Research Data might be shared, by whom, with whom, under what conditions, why, and to what effects. They are completed with answers to the questions: how? and where?
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Cai, Danlin, Mingyu Chen, Daxin zhu, and Junjie Liu. "Design of Intelligent Manufacturing Big Data Cloud Service Platform." MATEC Web of Conferences 153 (2018): 08005. http://dx.doi.org/10.1051/matecconf/201815308005.
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With the coming of the intelligent manufacturing, the technology and application of industrial big data will be popular in the future. The productivity, competitiveness and innovation of the manufacturing industries will be improved through the integrated innovation of big data technology and industries. Besides, products, production process, management, services, new form and new models will be more intellectualized. They will support the transformation and upgrading of manufacturing industry and the construction of an open, shared and collaborative ecological environment for intelligent manufacturing industry.
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Malar, Benjula Anbu, and Prabhu J. "Data Storage Security in the Cloud Environment Using the Honey Pot System." International Journal of e-Collaboration 16, no. 4 (October 2020): 1–14. http://dx.doi.org/10.4018/ijec.2020100101.
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Cloud computing is a framework for delivering services through a shared network. It should follow certain procedures or mechanisms to protect and make the cloud data more reliable. In secure cloud computing, the implementation and service delivery model are dealt with. Cloud security could be viewed as a provider and customer responsibility depending on their design and level. There are cases where multiple cloud users can use the same information to create service abnormalities, which is called ‘multitenancy.' In a multi-tenant model, the resources are isolated between different users and it is done by segmentation to achieve the goal of data security between many users. In the user access area, user access to common resources is also limited. The software is aware of the actions of the client and acts accordingly if unauthorized access is detected. The authors propose a clear idea of the data storage security of cloud information through honeypot in cloud monitoring applications and various cloud security scheme key models used and also identifies the audit time and invalid response time.