Relevant bibliographies by topics / Managed data

Academic literature on the topic 'Managed data'

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Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Managed data"

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Read, Chris. "Data: Embracing ‘managed ambiguity’." SecEd 2019, no. 15 (October 1, 2019): 30–31. http://dx.doi.org/10.12968/sece.2019.15.30.

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Schools should rethink their approaches to monitoring and evaluation and move away from meaningless and highly processed data in order to ease the work and accountability load. Chris Read looks at principles of how data should be used…
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Dempsey, P. "Managed chaos [data management]." Information Professional 2, no. 5 (October 1, 2005): 22–26. http://dx.doi.org/10.1049/inp:20050503.

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Benila S, Benila S., and Usha Bhanu N. Benila S. "Fog Managed Data Model for IoT based Healthcare Systems." 網際網路技術學刊 23, no. 2 (March 2022): 217–26. http://dx.doi.org/10.53106/160792642022032302003.

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<p>In Internet of things enabled healthcare system, sensors create vast volumes of data that are analyzed in the cloud. Transferring data from the cloud to the application takes a long time. An effective infrastructure can reduce latency and costs by processing data in real-time and close to the user devices. Fog computing can solve this issue by reducing latency by storing, processing, and analyzing patient data at the network edge. Placing the resources at fog layer and scheduling tasks is quite challenging in Fog computing. This paper proposes a Fog Managed Data Model (FMDM) with three layers namely Sensor, Fog and cloud to solve the aforementioned issue. Sensors generate patient data and that are managed and processed by Fog and cloud layers. Tasks are scheduled using a Weighted Fog Priority Job Scheduling algorithm (WFPJS) and fog nodes are allocated based on Priority based Virtual Machine Classification Algorithm (PVCA). The performance of this model is validated with static scheduling techniques with variable patient counts and network configurations. The proposed FMDM with WFPJS reduces response time, total execution cost, network usage, network latency, computational latency and energy consumption.</p> <p>&nbsp;</p>
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Zhang, Yuan, Yue Liu, and Zhong Tian Jia. "A Sensor Data Management Scheme for Wireless Sensor Networks." Key Engineering Materials 467-469 (February 2011): 709–12. http://dx.doi.org/10.4028/www.scientific.net/kem.467-469.709.

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One of the major difficulties of wireless sensor network (WSN) applications is how to efficiently manage the large amount of data produced by sensors. The differences from standard database source pose challenges of sensor data management. In this paper, we propose a novel sensor data management architecture based on our extensive discussion on existing works. The hierarchical system model consists of sensor network layer and proxy network layer. Sensor network layer performs limited computation and communication while being managed intelligently by the proxy network. The proxy network receives sensor data, manages sensor data and processes queries in a distributed manner. We also provide insight into possible research directions in this area.
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Lamest, Markus, and Mairead Brady. "Data-focused managerial challenges within the hotel sector." Tourism Review 74, no. 1 (February 4, 2019): 104–15. http://dx.doi.org/10.1108/tr-03-2017-0064.

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Purpose The purpose of this paper is to explore the managerial decision-making challenges of the use of data from online and offline customer data flooding into firms and managed through interactive dashboards. The paper provides insights into how managers within the hotel sector both manage and use the data as a core tool in discussions with finance managers/directors during negotiation on critical marketing investments. Design/methodology/approach The research design followed a multiple-case study design of five market-orientated hotels, which were selected as high performing data and dashboard users. Across each case company multiple informants were interviewed and shadowed, including marketing managers, general managers and finance managers/directors. There was also an in-depth investigation of the collection, dissemination and particularly use of traditional market research data and online data from social media sites, web sites and web and mobile analytics. This was augmented by a study of the customized, off site managed interactive databases, in use in all case companies. Findings This paper identifies managerial challenges experienced by general managers, marketing and financial managers using digital customer data. It investigated the power of the customer voice internally and found that unstructured qualitative data had greater visibility and usage once supported by a financial imperative. It also found that the use of interactive dashboards were a powerful manifestation of data technology use and increased marketing’s visibility, power and accountability within the firm. Research limitations/implications The paper provided a limited hotel perspective which impacts on generalizability. The findings should be tested quantitatively to ascertain their validity across a wider sector of businesses and operations. Though multiple site and cross-functional research adds value, one site might have provided more depth. Practical implications This paper reveals that managers need support in terms of time, resources and personnel to manage the flood of information into their organizations. It also suggested that general and marketing managers need to develop the skills to interpret the data for decision-making, so that the financial implications are understand. Originality/value Most social media studies within the hotel sector focus on the impact of social media reviews on consumer purchasing processes and/or on how managers communicate online with consumers. This paper takes an internal managerial perspective on data use for decision-making. This paper expands our understanding of marketing strategic decision-making through an in-depth exploration into how cross-functional decision-making uses contemporary customer data.
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Deleanides, Jessica, Kevin Gebhardt, Justin Hurd, and Clayton Stanley. "BIG DATA: CAN IT BE MANAGED?" Journal of Information Technology Education: Discussion Cases 5 (2016): 09. http://dx.doi.org/10.28945/3647.

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Justin Hurd, a regional manager for Marten Transport, Ltd. (Marten), knows that Marten’s data gathering initiative had produced a wealth of information related to these issues, but how could this data be transformed into useful, actionable metrics that could reduce inefficiencies and protect Marten’s bottom line?
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Slosar, J. R. "Trusting Managed Care: Unbiased Data Needed." Health Affairs 16, no. 3 (May 1997): 274–75. http://dx.doi.org/10.1377/hlthaff.16.3.274.

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Slosar, J. R. "Trusting Managed Care: Unbiased Data Needed." Health Affairs 16, no. 3 (May 1, 1997): 274–75. http://dx.doi.org/10.1377/hlthaff.16.3.274-a.

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Coulibaly, Moussa, Ahmed Errami, Sofia Belkhala, and Hicham Medromi. "A Live Smart Parking Demonstrator: Architecture, Data Flows, and Deployment." Energies 14, no. 7 (March 25, 2021): 1827. http://dx.doi.org/10.3390/en14071827.

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Smart Parking is essential for any future smart cities due to the tremendous growth of the car fleet. Such infrastructures require a certain amount of equipment. Indeed, smart parking integrates a lot of actors, to manage the parking its equipment must be managed accordingly. Here, is proposed a distributed architecture to manage them by collecting efficiently their data. Two types of data relating to the parking must be collected: those coming from the deployed equipment in the parking and those coming from the internet due to remote users. Thus, a system of two main servers based on the multi-agent concept is proposed. This system manages the parking platform. The first server is dedicated to the parking equipment data collection (Processing Server–PS). The second server (Processing Web Server–PWS) collects the users’ online data such as reservation, and it is responsible for pricing policies, and receive post-processed data from the Processing Server. The parking equipment integrates a lot of commercial solutions, an intelligent multi-platform application based on this two server philosophy is developed and can be used for parking operation by users and parking managers. The flowcharts of the agents from the two mains servers are presented. These flowcharts are currently used in our demonstrator and still under improvements. Here, we present the architecture (hardware and software) of our smart parking demonstrator developed by our department and suitable for the experimentation of our future work related to this hot topic.
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Zacharopoulos, Theologos, Pablo Inostroza, and Tijs van der Storm. "Extensible modeling with managed data in Java." ACM SIGPLAN Notices 52, no. 3 (May 12, 2017): 25–35. http://dx.doi.org/10.1145/3093335.2993240.

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Dissertations / Theses on the topic "Managed data"

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Deb, Debzani. "Achieving self-managed deployment in a distributed environment via utility functions." Thesis, Montana State University, 2008. http://etd.lib.montana.edu/etd/2008/deb/DebD0508.pdf.

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This dissertation presents algorithms and mechanisms that enable self-managed, scalable and efficient deployment of large-scale scientific and engineering applications in a highly dynamic and unpredictable distributed environment. Typically these applications are composed of a large number of distributed components and it is important to meet the computational power and network bandwidth requirements of those components and their interactions. However satisfying these requirements in a large-scale, shared, heterogeneous, and highly dynamic distributed environment is a significant challenge. As systems and applications grow in scale and complexity, attaining the desired level of performance in this uncertain environment using current approaches based on global knowledge, centralized scheduling and manual reallocation becomes infeasible. This dissertation focuses on the modeling of the application and underlying architecture into a common abstraction and on the incorporations of autonomic features into those abstractions to achieve self-managed deployment. In particular, we developed techniques for automatically identifying application components and their estimated resource requirements within an application and used them in order to model the application into a graph abstraction. We also developed techniques that allow the distributed resources to self-organize in a utility-aware way while assuming minimal knowledge about the system. Finally, to achieve self-managed deployment of application components to the distributed nodes, we designed a scalable and adaptive scheduling algorithm which is governed by a utility function. The utility function, which combines several application and system level attributes, governs both the initial deployment of the application components and their reconfigurations despite the dynamism and uncertainty associated with the computing environment. The experimental results show that it is possible to achieve and maintain efficient deployment by applying the utility function derived in this paper based solely on locally available information and without costly global communication or synchronization. The self-management is therefore decentralized and provides better adaptability, scalability and robustness.
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Loudon, Melissa. "Data management and reporting for drinking water quality monitoring in community-managed supplies." Master's thesis, University of Cape Town, 2007. http://hdl.handle.net/11427/5031.

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Includes bibliographical references (leaves 111-126).
Water Service Authorities, which may be district municipalities with hundreds of community-managed supplies under their jurisdiction, are legally responsible for ensuring the quality of water supplied to all consumers. Without the assistance of communities, this requirement, which would involve regular testing in many remote and inaccessible supplies, is extremely difficult to fulfil. Water Service Authorities also struggle to respond timeously to problems in remote supplies, as they are often unaware of the problem for some days. Two-way communication between the Water Service Authority and the Community-based Water Services Provider is therefore essential to an effective monitoring programme. Information and communication technologies, particularly mobile phones on the cellular network, offer potential solution to the challenge of supporting community-managed supplies. Following an investigation into the information needs of various stakeholders in community management, a prototype drinking water quality information system for community-managed supplies was developed.
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Yeom, Jae-seung. "Optimizing Data Accesses for Scaling Data-intensive Scientific Applications." Diss., Virginia Tech, 2014. http://hdl.handle.net/10919/64180.

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Data-intensive scientific applications often process an enormous amount of data. The scalability of such applications depends critically on how to manage the locality of data. Our study explores two common types of applications that are vastly different in terms of memory access pattern and workload variation. One includes those with multi-stride accesses in regular nested parallel loops. The other is for processing large-scale irregular social network graphs. In the former case, the memory location or the data item accessed in a loop is predictable and the load on processing a unit work (an array element) is relatively uniform with no significant variation. On the other hand, in the latter case, the data access per unit work (a vertex) is highly irregular in terms of the number of accesses and the locations being accessed. This property is further tied to the load and presents significant challenges in the scalability of the application performance. Designing platforms to support extreme performance scaling requires understanding of how application specific information can be used to control the locality and improve the performance. Such insights are necessary to determine which control and which abstraction to provide for interfacing an underlying system and an application as well as for designing a new system. Our goal is to expose common requirements of data-intensive scientific applications for scalability. For the former type of applications, those with regular accesses and uniform workload, we contribute new methods to improve the temporal locality of software-managed local memories, and optimize the critical path of scheduling data transfers for multi-dimensional arrays in nested loops. In particular, we provide a runtime framework allowing transparent optimization by source-to-source compilers or automatic fine tuning by programmers. Finally, we demonstrate the effectiveness of the approach by comparing against a state-of-the-art language-based framework. For the latter type, those with irregular accesses and non-uniform workload, we analyze how the heavy-tailed property of input graphs limits the scalability of the application. Then, we introduce an application-specific workload model as well as a decomposition method that allows us to optimize locality with the custom load balancing constraints of the application. Finally, we demonstrate unprecedented strong scaling of a contagion simulation on two state-of-the-art high performance computing platforms.
Ph. D.
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Johansson, Tobias. "Managed Distributed TensorFlow with YARN : Enabling Large-Scale Machine Learning on Hadoop Clusters." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-248007.

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Apache Hadoop is the dominant open source platform for the storage and processing of Big Data. With the data stored in Hadoop clusters, it is advantageous to be able to run TensorFlow applications on the same cluster that holds the input data sets for training machine learning models. TensorFlow supports distributed executions where Deep Neural Networks can be trained utilizing a large amount of compute nodes. To configure and launch distributed TensorFlow applications manually is complex and impractical, and gets worse with more nodes. This project presents a framework that utilizes Hadoop’s resource manager YARN to manage distributed TensorFlow applications. The proposal is a native YARN application with one ApplicationMaster (AM) per job, utilizing the AM as a registry for discovery prior to job execution. Conforming TensorFlow code to the framework typically is about a few lines of code. In comparison to TensorFlowOnSpark, the user experience is very similar, and collected performance data indicates that there exists an advantage of running TensorFlow directly on YARN with no extra layer in between.
Apache Hadoop är den ledande öppen källkod-plattformen för lagringen och processeringen av big data. Med data lagrat i Hadoop-kluster, är det fördelaktigt att kunna köra TensorFlow-applikationer på samma kluster som håller ingående dataset för träning av maskininlärningsmodeller. TensorFlow stödjer distribuerade exekveringar där djupa neurala nätverk kan tränas genom att använda en stor mängd berräkningsnoder. Att konfigurera och starta distribuerade TensorFlowapplikationer manuellt är komplext och opraktiskt och blir värre med fler noder.Detta projekt presenterar ett ramverk som använder Hadoops resurhanterare YARN för att hantera distribuerade TensorFlow-applikationer. Förslaget är en hemmahörande YARN-applikation med en ApplicationMaster (AM) per jobb som använder AM som ett register för upptäckt innan jobbet körs. Att anpassa TensorFlow-kod till ramverket handlar typiskt om några rader kod. I jämförelse med TensorFlowOnSpark är användarupplevelse väldigt likt och insamlad prestandadata indikerar att det finns en fördel med att köra TensorFlow direkt på YARN utan något extra lager däremellan.
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Lienhard, Jasper Z. (Jasper Zebulon). "What is measured is managed : statistical analysis of compositional data towards improved materials recovery." Thesis, Massachusetts Institute of Technology, 2015. http://hdl.handle.net/1721.1/98661.

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Thesis: S.B., Massachusetts Institute of Technology, Department of Materials Science and Engineering, 2015.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 35-36).
As materials consumption increases globally, minimizing the end-of-life impact of solid waste has become a critical challenge. Cost-effective methods of quantifying and tracking municipal solid waste contents and disposal processes are necessary to drive and track increases in material recovery and recycling. This work presents an algorithm for estimating the average quantity and composition of municipal waste produced by individual locations. Mass fraction confidence intervals for different types of waste were calculated from data collected by sorting and weighing waste samples from municipal sites. This algorithm recognizes the compositional nature of mass fraction waste data. The algorithm developed in this work also evaluated the value of additional waste samples in refining mass fraction confidence intervals. Additionally, a greenhouse gas emissions model compared carbon dioxide emissions for different disposal methods of waste, in particular landfilling and recycling, based on the waste stream. This allowed for identification of recycling opportunities based on carbon dioxide emission savings from offsetting the need for primary materials extraction. Casework was conduced with this methodology using site-specific waste audit data from industry. The waste streams and carbon dioxide emissions of three categories of municipal waste producers, retail, commercial, and industrial, were compared. Paper and plastic products, whose mass fraction averages ranged from 40% to 52% and 26% to 29%, respectively, dominated the waste streams of these three industries. Average carbon dioxide emissions in each of these three industries ranged from 2.18 kg of CO₂ to 2.5 kg of CO₂ per kilogram of waste thrown away. On average, Americans throw away about 2 kilograms per person per day of solid waste.
by Jasper Z. Lienhard.
S.B.
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Nilsson, Maximiliam, and Gusten Hansson. "Are Mutual Fund Managers’ Compensation Reasonable In Relation To Their Contributions? : - A study regarding actively managed mutual funds." Thesis, Linnéuniversitetet, Institutionen för nationalekonomi och statistik (NS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-96945.

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This thesis aims to investigate fund managers salaries in relation to their contributions. The study is conducted on the Swedish fund market under a period over five years, 2014-2018, and include 332 funds. The result observed shows a positive relation between salaries and risk-adjusted performance. The result proves that fund managers are able to outperform the market on average, which should not be possible to do systematically over time according to the efficient market hypothesis. It also turns out that salary has a positive relationship with assets under management. This indicates that fund managers are employed and compensated for more reasons than to generate a high return, namely to contribute to more significant inflows of cash to the fund company. Interpretations of fund managers’ salaries are primarily linked to agency theory and economics of superstars. The agency problem alter in the fund industry since the setting is two-folded. Agency problem could be mitigated by implementing a performance-based compensation structure, to aligning investors, management and fund managers’ ambitions. The result shows signs that a performance-based salary is present in the fund industry. A fund managers’ salary assumes to be based on his/her skillfulness, but could also be due to an individual’s stardom. To conclude, the thesis state that fund managers’ deserve their salary, which in relative terms are fairly high, since they procure additional benefits to the fund company.
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Salim, Christian. "Data Reduction based energy-efficient approaches for secure priority-based managed wireless video sensor networks." Thesis, Bourgogne Franche-Comté, 2018. http://www.theses.fr/2018UBFCD052/document.

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L'énorme quantité de données dans les réseaux de capteurs vidéo sans fil (WVSN) pour les nœuds de capteurs de ressources limitées augmente les défis liés à la consommation d'énergie et à la consommation de bande passante. La gestion du réseau est l’un des défis de WMSN en raison de l’énorme quantité d’images envoyées simultanément par les capteurs au coordinateur. Dans cette thèse, pour surmonter ces problèmes, plusieurs contributions ont été apportées. Chaque contribution se concentre sur un ou deux défis, comme suit: Dans la première contribution, pour réduire la consommation d'énergie, une nouvelle approche pour l'agrégation des données dans WVSN basée sur des fonctions de similarité des plans est proposée. Il est déployé sur deux niveaux: le niveau du nœud du capteur vidéo et le niveau du coordinateur. Au niveau du nœud de capteur, nous proposons une technique d'adaptation du taux de trame et une fonction de similarité pour réduire le nombre de trames détectées par les nœuds de capteur et envoyées au coordinateur. Au niveau du coordinateur, après avoir reçu des plans de différents nœuds de capteurs voisins, la similarité entre ces plans est calculée pour éliminer les redondances. Dans la deuxième contribution, certains traitements et analyses sont ajoutés en fonction de la similarité entre les images au niveau du capteur-nœud pour n'envoyer que les cadres importants au coordinateur. Les fonctions cinématiques sont définies pour prévoir l'étape suivante de l'intrusion et pour planifier le système de surveillance en conséquence. Dans la troisième contribution, sur la phase de transmission, au niveau capteur-nœud, un nouvel algorithme d'extraction des différences entre deux images est proposé. Cette contribution prend également en compte le défi de sécurité en adaptant un algorithme de chiffrement efficace au niveau du nœud de capteur. Dans la dernière contribution, pour éviter une détection plus lente des intrusions conduisant à des réactions plus lentes du coordinateur, un protocole mac-layer basé sur le protocole S-MAC a été proposé pour contrôler le réseau. Cette solution consiste à ajouter un bit de priorité au protocole S-MAC pour donner la priorité aux données critiques
The huge amount of data in Wireless Video Sensor Networks (WVSNs) for tiny limited resources sensor nodes increases the energy and bandwidth consumption challenges. Controlling the network is one of the challenges in WMSN due to the huge amount of images sent at the same time from the sensors to the coordinator. In this thesis, to overcome these problems, several contributions have been made. Each contribution concentrates on one or two challenges as follows: In the first contribution, to reduce the energy consumption a new approach for data aggregation in WVSN based on shot similarity functions is proposed. It is deployed on two levels: the video-sensor node level and the coordinator level. At the sensor node level, we propose a frame rate adaptation technique and a similarity function to reduce the number of frames sensed by the sensor nodes and sent to the coordinator. At the coordinator level, after receiving shots from different neighboring sensor nodes, the similarity between these shots is computed to eliminate redundancies. In the second contribution, some processing and analysis are added based on the similarity between frames on the sensor-node level to send only the important frames to the coordinator. Kinematic functions are defined to predict the next step of the intrusion and to schedule the monitoring system accordingly. In the third contribution, on the transmission phase, on the sensor-node level, a new algorithm to extract the differences between two images is proposed. This contribution also takes into account the security challenge by adapting an efficient ciphering algorithm on the sensor node level. In the last contribution, to avoid slower detection of intrusions leading to slower reactions from the coordinator, a mac-layer protocol based on S-MAC protocol has been proposed to control the network. This solution consists in adding a priority bit to the S-MAC protocol to give priority to critical data
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Muthuswamy, Sunil. "System implementation of a real-time, content based application router for a managed publish-subscribe system." Online access for everyone, 2008. http://www.dissertations.wsu.edu/Thesis/Summer2008/S_Muthuswamy_080408.pdf.

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Luong, Johannes [Verfasser], Wolfgang [Gutachter] Lehner, and Ziawasch [Gutachter] Abedjan. "A Common Programming Interface for Managed Heterogeneous Data Analysis / Johannes Luong ; Gutachter: Wolfgang Lehner, Ziawasch Abedjan." Dresden : Technische Universität Dresden, 2021. http://d-nb.info/1238140599/34.

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Boland, Samuel James. "Hydrologic and biogeochemical signatures in intensively managed catchments: data synthesis and development of a passive surfacewater quality sampler." Thesis, University of Iowa, 2011. https://ir.uiowa.edu/etd/1205.

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This study presents a conjunctive data synthesis and technology development approach to aid in enhancing understanding of the scaling behavior of water flow and nutrient transport in intensively managed agricultural catchments. Anthropogenic modifications to the landscape, with agricultural activities being a primary driver, have resulted in significant alterations to hydrologic and biogeochemical cycles. Significant research has been directed towards understanding and predicting the changes in these cycles in an effort to mitigate the associated adverse effects. Typical modeling efforts suffer from scaling issues associated with heterogeneities that arise at the catchment scale. New parsimonious approaches that rely on emergent patterns in data have been proposed to aid current modeling efforts. This study adopts a data synthesis approach to identify emergent patterns in hydrologic and nitrogen solute behavior in the context of agricultural activities at the catchment scale. The results of the synthesis indicate a strong anthropogenic signature in agricultural landscapes through (a) decrease in variability in the streamflow distribution with increase in the proportion of the catchment that is artificially drained and (b) relatively low variability in nitrogen concentration relative to discharge. Due to the dependence of such data synthesis methods on reliable data, a new method of data collection, through the use of an innovative passive sampling device, is developed to aid in future data synthesis and subsequent modeling efforts. Initial laboratory studies towards the development of the device achieved in this thesis indicate its ability to capture flow-averaged solute concentration over a specified deployment period. Future work involves testing the device under various field deployment conditions. The relatively low cost of the device would enable the estimation of spatially distributed flow-averaged concentrations that would complement existing costlier measurement methods, and significantly aid future modeling efforts and management decisions.
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Books on the topic "Managed data"

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New York (State). Division of Management Audit and State Financial Services. Department of Health, Medicaid managed care encounter data. [Albany, N.Y: The Division, 2002.

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1952-, Bernhardt Victoria L., ed. Data analysis for continuous school improvement. 2nd ed. Larchmont, NY: Eye On Education, 2004.

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Administration, United States Health Care Financing. Medicaid-medicare common data initiative: A core data set for states and medicaid managed care plans. [Baltimore, Md.?: Health Care Financing Administration, 1994.

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United States. Health Care Financing Administration. Medicaid-medicare common data initiative: A core data set for states and medicaid managed care plans. [Baltimore, Md.?: Health Care Financing Administration, 1994.

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Administration, United States Health Care Financing. Medicaid-medicare common data initiative: A core data set for states and medicaid managed care plans. [Baltimore, Md.?: Health Care Financing Administration, 1994.

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United States. Health Care Financing Administration. Medicaid-medicare common data initiative: A core data set for states and medicaid managed care plans. [Baltimore, Md.?: Health Care Financing Administration, 1994.

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United States. Health Care Financing Administration. Medicaid-medicare common data initiative: A core data set for states and medicaid managed care plans. [Baltimore, Md.?: Health Care Financing Administration, 1994.

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Medicaid-medicare common data initiative: A core data set for states and medicaid managed care plans. [Baltimore, Md.?: Health Care Financing Administration, 1994.

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United States. Health Care Financing Administration. Medicaid-medicare common data initiative: A core data set for states and medicaid managed care plans. [Baltimore, Md.?: Health Care Financing Administration, 1994.

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Great teaching in the one-computer classroom. 5th ed. Watertown, MA: Tom Snyder Productions, 1998.

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Book chapters on the topic "Managed data"

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Boele, Thomas. "Beitrag der WAN Acceleration für Data Protection, IT-Konsolidierung und Cloud Computing." In Managed Services, 355–64. Wiesbaden: Gabler, 2009. http://dx.doi.org/10.1007/978-3-8349-8290-2_16.

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Ezzio, David. "Enhanced Classes and Managed Fields." In Using and Understanding Java Data Objects, 143–83. Berkeley, CA: Apress, 2003. http://dx.doi.org/10.1007/978-1-4302-0767-2_5.

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Ross, Brandon, Engin Arslan, Bing Zhang, and Tevfik Kosar. "Managed File Transfer as a Cloud Service." In Cloud Computing for Data-Intensive Applications, 379–99. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-1905-5_16.

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Burine, Lotina, Daniel Polónia, and Adriana Gradim. "How Health Data Are Managed in Mozambique." In Advances in Intelligent Systems and Computing, 385–93. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72651-5_37.

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Challa, Siva, and Artur Laksberg. "Data Marshaling between COM and.NET." In Essential Guide to Managed Extensions for C++, 261–77. Berkeley, CA: Apress, 2002. http://dx.doi.org/10.1007/978-1-4302-0834-1_19.

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Weissman, Ben, and Anthony E. Nocentino. "Deploying an Azure Arc-enabled SQL Managed Instance." In Azure Arc-enabled Data Services Revealed, 121–47. Berkeley, CA: Apress, 2022. http://dx.doi.org/10.1007/978-1-4842-8085-0_7.

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Weissman, Ben, and Anthony E. Nocentino. "Deploying an Azure Arc-Enabled SQL Managed Instance." In Azure Arc-Enabled Data Services Revealed, 85–96. Berkeley, CA: Apress, 2021. http://dx.doi.org/10.1007/978-1-4842-6705-9_5.

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Mamei, Marco, and Franco Zambonelli. "Self-Maintaining Overlay Data Structures for Pervasive Autonomic Services." In Self-Managed Networks, Systems, and Services, 58–72. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11767886_5.

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Wilson, Lucas A. "Using Managed High Performance Computing Systems for High-Throughput Computing." In Conquering Big Data with High Performance Computing, 61–79. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-33742-5_4.

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Alboaie, Sinică, and Doina Cosovan. "Private Data System Enabling Self-Sovereign Storage Managed by Executable Choreographies." In Distributed Applications and Interoperable Systems, 83–98. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-59665-5_6.

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Conference papers on the topic "Managed data"

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Loh, Alex, Tijs van der Storm, and William R. Cook. "Managed data." In the ACM international symposium. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2384592.2384609.

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Jackson, Adrian, and Par Strand. "MDMP: Managed Data Message Passing." In 2013 15th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC). IEEE, 2013. http://dx.doi.org/10.1109/synasc.2013.71.

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Deshpande, Umesh, Nick Linck, and Sangeetha Seshadri. "Self managed data protection for containers." In SYSTOR '21: The 14th ACM International Systems and Storage Conference. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3456727.3463833.

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Wagner, Rick, Philip Papadopoulos, Dmitry Mishin, Trevor Cooper, Mahidhar Tatineti, Gregor von Laszewski, Fugang Wang, and Geoffrey C. Fox. "User Managed Virtual Clusters in Comet." In XSEDE16: Diversity, Big Data, and Science at Scale. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2949550.2949555.

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Barczyk, Artur, Azher Mughal, Harvey Newman, Iosif Legrand, Michael Bredel, Ramiro Voicu, Vlad Lapadatescu, and Tony Wildish. "Towards Managed Terabit/s Scientific Data Flows." In 2014 Fourth International Workshop on Network-Aware Data Management (NDM). IEEE, 2014. http://dx.doi.org/10.1109/ndm.2014.8.

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Renjish Kumar, K. R. "International mobile data roaming: Managed or unmanaged?" In 2010 9th Conference on Telecommunications Internet and Media Techno-Economics (CTTE). IEEE, 2010. http://dx.doi.org/10.1109/ctte.2010.5557699.

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Wesolowski, Carl, and Robert J. Madeira. "Quality is Managed by Better Data Utilization." In HT2019. ASM International, 2019. http://dx.doi.org/10.31399/asm.cp.ht2019p0070.

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Abstract Teams of people in most every company are focused on expanding and improving the utilization of data from the manufacturing and shop floors. While there are multiple benefits that accrue from each new successful initiative including part traceability records and process trending. The driving imperative is quality improvement. Data capture, feedback systems, real time analysis and data archiving capabilities are all contributors to a Heat Treat Management Audit System that delivers tangible results. For the year 2016, US - based OEM’s and Suppliers reported paying approximately $11.8 billion in claims, and recorded $10.3 billion of warranty and recall accruals. This is a 300% increase in what was paid out and accrued for in 2013. [1] Familiar buzz words in quality management, CQI-9, ISO 9001, SPC, and TS 16949 are written on the walls of both manufacturing and engineering departments. This presentation explains these acronyms and how these standards construct the boundaries of an effective Quality Improvement System.
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Jablin, Thomas B., James A. Jablin, Prakash Prabhu, Feng Liu, and David I. August. "Dynamically managed data for CPU-GPU architectures." In the Tenth International Symposium. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2259016.2259038.

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Zacharopoulos, Theologos, Pablo Inostroza, and Tijs van der Storm. "Extensible modeling with managed data in Java." In GPCE '16: Generative Programming: Concepts and Experiences. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2993236.2993240.

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Zhao, Liang, Sherif Sakr, Alan Fekete, Hiroshi Wada, and Anna Liu. "Application-Managed Database Replication on Virtualized Cloud Environments." In 2012 IEEE International Conference on Data Engineering Workshops (ICDEW). IEEE, 2012. http://dx.doi.org/10.1109/icdew.2012.77.

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Reports on the topic "Managed data"

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Gayek, P., and S. Nix. Definitions of Managed Objects for Data Link Switching using SMIv2. Edited by D. Chen. RFC Editor, October 1996. http://dx.doi.org/10.17487/rfc2024.

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Nix, S., and A. Bartky. Definitions of Managed Objects for SNA Data Link Control (SDLC) using SMIv2. Edited by W. Clark. Chair J. Hilgeman. RFC Editor, January 1995. http://dx.doi.org/10.17487/rfc1747.

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Smith, M. L., S. Hostetler, and J. Northey. Managed Aquifer Recharge prospectivity mapping in the Northern Territory arid zone using remotely sensed data. Geoscience Australia, 2020. http://dx.doi.org/10.11636/132540.

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Libra, Jesse Madden, and María Alejandra Baquero. FS 1.1: Water access in Latin America and the Caribbean: Definitions and Data. Inter-American Development Bank, October 2022. http://dx.doi.org/10.18235/0004493.

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Universal access to safely managed drinking water by 2030 is a key goal under the 2030 UN Agenda. This fact sheet describes definitions related to safely managed drinking water as defined by the Joint Monitoring Programme and describes their status in Latin America and the Caribbean using data from the 2018/19 AmericasBarometer survey.
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Kenny, F., D. Conrod, G. Gallant, B. Smith, S. MacRitchie, and D. Grgic. Near real-time water quantity monitoring data assets collected, managed, analyzed and disseminated by the MNRF and MOECC. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2016. http://dx.doi.org/10.4095/297731.

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Soriano, C., R. Rossi, and Q. Ayoul-Guilmard. D8.1 Data Management Plan. Scipedia, 2021. http://dx.doi.org/10.23967/exaqute.2021.2.019.

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The ExaQUte project participates in the Pilot on Open Research Data launched by the European Commission (EC) along with the H2020 program. This pilot is part of the Open Access to Scientific Publications and Research Data program in H2020. The goal of the program is to foster access to research data generated in H2020 projects. The use of a Data anagement Plan (DMP) is required for all projects participating in the Open Research Data Pilot, in which they will specify what data will be kept for the longer term. The underpinning idea is that Horizon 2020 beneficiaries have to make their research data findable, accessible, interoperable and re-usable (FAIR), to ensure it is soundly managed.
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Oliver, Amanda, William Slack, and Alan Katzenmeyer. Occurrence of silver, bighead, and black carp in waters managed by the US Army Corps of Engineers -- geospatial data appendix. Engineer Research and Development Center (U.S.), August 2022. http://dx.doi.org/10.21079/11681/44984.

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Ayers, R., G. P. Course, and G. R. Pasco. Scottish Inshore Fisheries Integrated Data System (SIFIDS): work package (2) final report WP2A: development and pilot deployment of a prototypic autonomous fisheries data harvesting system, and WP2B: investigation into the availability and adaptability of novel technological approaches to data collection. Edited by Mark James and Hannah Ladd-Jones. Marine Alliance for Science and Technology for Scotland (MASTS), 2019. http://dx.doi.org/10.15664/10023.23443.

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[Extract from Executive Summary] To enhance sustainability and foster resilience within Scotland’s inshore fishing communities an effective system of collecting and sharing relevant data is required. To support business decisions made by vessel owners as well as informing fisheries managers and those involved in marine planning it will be vital to collect a range of information which will provide a robust understanding of fishing activity, the economic value of the sector and its importance within local communities. The SIFIDS Project was conceived to assist in attaining these goals by working alongside fishers to develop and test technology to automatically collect and collate data on board vessels, thereby reducing the reporting burden on fishers. The project built upon previous research funded through the European Fisheries Fund (EFF) and was designed to deliver a step change in the way that inshore fisheries in Scotland could be managed in cooperation with the industry. The project focussed on inshore fishing vessels around Scotland, where spatio-temporal information on the distribution of vessels and associated fishing effort is data deficient. The whole project was broken down into 12 highly integrated work packages. This is the integrated report for work packages 2A and 2B, entitled’ Development and Pilot Deployment of a Prototypic Autonomous Fisheries Data Harvesting System’ (2A) and ‘Investigation into the Availability and Adaptability of Novel Technological Approaches to Data Collection’ (2B).
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Schoening, Timm. PyQuickMaps. GEOMAR, 2021. http://dx.doi.org/10.3289/sw_4_2021.

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A slim python library to link maps and sampling data with prediction methods. PyQuickMaps can do interpolation (with scipy.interpolate.griddata), kriging (with pykrige) and random forest regression (with sklearn.ensemble.RandomForestRegressor). It also features plotting nice geographical maps with matplotlib and storing those to geotiff with rasterio. Coordinate transforms are managed internally with osgeo/gdal.
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Josey, Colin, and Jeremy Conlin. LANL Nuclear Data Manager Format Specification v1.0. Office of Scientific and Technical Information (OSTI), August 2022. http://dx.doi.org/10.2172/1880470.

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