Academic literature on the topic 'Coverage problem'

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Journal articles on the topic "Coverage problem"

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Murray, Alan T. "Maximal Coverage Location Problem." International Regional Science Review 39, no. 1 (December 9, 2015): 5–27. http://dx.doi.org/10.1177/0160017615600222.

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Zhang, Guo-Qiang, and Licong Cui. "A set coverage problem." Information Processing Letters 110, no. 4 (January 2010): 158–59. http://dx.doi.org/10.1016/j.ipl.2009.11.012.

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Khuller, Samir, Anna Moss, and Joseph (Seffi) Naor. "The budgeted maximum coverage problem." Information Processing Letters 70, no. 1 (April 1999): 39–45. http://dx.doi.org/10.1016/s0020-0190(99)00031-9.

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Chi, D. T., and Y. T. Su. "On a satellite coverage problem." IEEE Transactions on Aerospace and Electronic Systems 31, no. 3 (July 1995): 891–96. http://dx.doi.org/10.1109/7.395249.

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Davoodi, Mansoor, and Ali Mohades. "Solving the constrained coverage problem." Applied Soft Computing 11, no. 1 (January 2011): 963–69. http://dx.doi.org/10.1016/j.asoc.2010.01.016.

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Cohen, Reuven, and Liran Katzir. "The Generalized Maximum Coverage Problem." Information Processing Letters 108, no. 1 (September 2008): 15–22. http://dx.doi.org/10.1016/j.ipl.2008.03.017.

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Shakhatreh, Hazim, Abdallah Khreishah, and Issa Khalil. "Indoor Mobile Coverage Problem Using UAVs." IEEE Systems Journal 12, no. 4 (December 2018): 3837–48. http://dx.doi.org/10.1109/jsyst.2018.2824802.

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SHAHABUDIN, S. H. "Content coverage in problem-based learning." Medical Education 21, no. 4 (July 1987): 310–13. http://dx.doi.org/10.1111/j.1365-2923.1987.tb00369.x.

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Levinson, Gershon, and Sol Shnider. "Obstetric Anesthesia Coverage-A Continuing Problem." Anesthesiology 65, no. 3 (September 1, 1986): 245–46. http://dx.doi.org/10.1097/00000542-198609000-00001.

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Shetty, Bala, Rathindra Sarathy, and Arun Sen. "The K-coverage concentrator location problem." Applied Mathematical Modelling 16, no. 2 (February 1992): 94–100. http://dx.doi.org/10.1016/0307-904x(92)90086-i.

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Dissertations / Theses on the topic "Coverage problem"

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Hoesel, Stan Van, and Albert Wagelmans. "On the P-coverage Problem on the Real Line." Massachusetts Institute of Technology, Operations Research Center, 1991. http://hdl.handle.net/1721.1/5221.

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Abstract: In this paper we consider the p-coverage problem on the real line. We first give a detailed description of an algorithm to solve the coverage problem without the upper bound p on the number of open facilities. Then we analyze how the structure of the optimal solution changes if the setup costs of the facilities are all decreased by the same amount. This result is used to develop a parametric approach to the p-coverage problem which runs in O(pnlogn) time, n being the number of clients. OR/MS subject classification: Analysis of algorithms, computational complexity: parametric application of dynamic programming; Dynamic programming/optimal control, applications: parametric approach to p-coverage problem on the real line; Facilities/equipment planning, location, discrete: p-coverage problem on the real line.
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Baydogan, Mustafa Gokce. "Energy Efficient Coverage And Connectivity Problem In Wireless Sensor Networks." Master's thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/12609688/index.pdf.

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In this thesis, we study the energy efficient coverage and connectivity problem in wireless sensor networks (WSNs). We try to locate heterogeneous sensors and route data generated to a base station under two conflicting objectives: minimization of network cost and maximization of network lifetime. We aim at satisfying connectivity and coverage requirements as well as sensor node and link capacity constraints. We propose mathematical formulations and use an exact solution approach to find Pareto optimal solutions for the problem. We also develop a multiobjective genetic algorithm to approximate the efficient frontier, as the exact solution approach requires long computation times. We experiment with our genetic algorithm on randomly generated problems to test how well the heuristic procedure approximates the efficient frontier. Our results show that our genetic algorithm approximates the efficient frontier well in reasonable computation times.
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Sambhara, Chaitanya. "P-Percent Coverage in Wireless Sensor Networks." Digital Archive @ GSU, 2008. http://digitalarchive.gsu.edu/cs_theses/56.

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Coverage in a Wireless Sensor Network reflects how well a sensor network monitors an area. Many times it is impossible to provide full coverage. The key challenges are to prolong the lifetime and ensure connectivity to provide a stable network. In this thesis we first define p-percent coverage problem in which we require only p% of the whole area to be monitored. We propose two algorithms, Connected P-Percent Coverage Depth First Search (CpPCA-DFS) and Connected P-Percent Connected Dominating Set (CpPCA-CDS). Through simulations we then compare and analyze them for their efficiency and lifetime. Finally in conclusion we prove that CpPCA-CDS provides 5 to 20 percent better active node ratio at low density. At high node density it achieves better distribution of covered area however the lifetime is only 5 to10 percent shorter then CpPCA-DFS. Overall CpPCA-CDS provides up to 30 percent better distribution of covered area.
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Orbay, Berk. "An Interactive Evolutionary Algorithm For The Multiobjective Relocation Problem With Partial Coverage." Master's thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12613196/index.pdf.

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In this study, a bi-objective capacitated facility location problem is presented which includes partial coverage concept and relocation of facility nodes. In partial coverage, a predefined distance between a demand node and a facility node is assumed to be fully covered. After the predefined distance, the service level commences to decay linearly. The problem is designed to consider the existence of already functioning facility nodes. It is allowed to close these existing facilities and open new facilities in potential sites. However, existing facility nodes are strongly favored against new facility nodes. The objectives are the maximization of the weighted total coverage and the minimization of number of facility nodes. A novel interactive multi-objective evolutionary algorithm is proposed to solve this problem, I-TREA. I-TREA is originated from NSGA-II and designed for interactive methods benefiting from quality infeasible solutions. The performance of I-TREA is benchmarked with a modified version of NSGA-II on randomly generated problems with various sizes and utility functions.
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Yin, Li. "Sensor network coverage and data aggregation problem: solutions toward the maximum lifetime." Diss., Rolla, Mo. : University of Missouri-Rolla, 2007. http://scholarsmine.mst.edu/thesis/pdf/Yin_09007dcc803c1aa0.pdf.

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Thesis (M.S.)--University of Missouri--Rolla, 2007.
Vita. The entire thesis text is included in file. Title from title screen of thesis/dissertation PDF file (viewed November 26, 2007) Includes bibliographical references (p. 51-55).
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Vu, Chinh Trung. "An Energy-Efficient Distributed Algorithm for k-Coverage Problem in Wireless Sensor Networks." Digital Archive @ GSU, 2007. http://digitalarchive.gsu.edu/cs_theses/40.

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Wireless sensor networks (WSNs) have recently achieved a great deal of attention due to its numerous attractive applications in many different fields. Sensors and WSNs possesses a number of special characteristics that make them very promising in many applications, but also put on them lots of constraints that make issues in sensor network particularly difficult. These issues may include topology control, routing, coverage, security, and data management. In this thesis, we focus our attention on the coverage problem. Firstly, we define the Sensor Energy-efficient Scheduling for k-coverage (SESK) problem. We then solve it by proposing a novel, completely localized and distributed scheduling approach, naming Distributed Energy-efficient Scheduling for k-coverage (DESK) such that the energy consumption among all the sensors is balanced, and the network lifetime is maximized while still satisfying the k-coverage requirement. Finally, in related work section we conduct an extensive survey of the existing work in literature that focuses on with the coverage problem.
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Toreyen, Ozgun. "Hierarchical Maximal Covering Location Problem With Referral In The Presence Of Partial Coverage." Master's thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/12608771/index.pdf.

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We consider a hierarchical maximal covering location problem to locate p health centers and q hospitals in such a way that maximum demand is covered, where health centers and hospitals have successively inclusive hierarchy. Demands are 3 types: demand requiring low-level service only, demand requiring high-level service only, and demand requiring both levels of service at the same time. All types of requirements of a demand point should be either covered by hospital providing both levels of service or referred to hospital via health center since a demand point is not covered unless all levels of requirements are satisfied. Thus, a health center cannot be opened unless it is suitable to refer its covered demand to a hospital. Referral is defined as coverage of health centers by hospitals. We also added partial coverage to this complex hierarchic structure, that is, a demand point is fully covered up to the minimum critical distance, non-covered after the maximum critical distance and covered with a decreasing quality while increasing distance to the facility between minimum and maximum critical distances. We developed an MIP formulation to solve the Hierarchical Maximal Covering Location Problem with referral in the presence of partial coverage. We solved small-size problems optimally using GAMS. For large-size problems we developed a Genetic Algorithm that gives near-optimal results quickly. We tested our Genetic Algorithm on randomly generated problems of sizes up to 1000 nodes.
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Hsieh, Pei-Shan, and Pei-Shan Hsieh. "Investigating the Maximal Coverage by Point-based Surrogate Model for Spatial Facility Location Problem." Diss., The University of Arizona, 2016. http://hdl.handle.net/10150/623182.

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Spatial facility location problems (SFLPs) involve the placement of facilities in continuous demand regions. One approach to solving SFLPs is to aggregate demand into discrete points, and then solve the point-based model as a conventional facility location problem (FLP) according to a surrogate model. Solution performance is measured in terms of the percentage of continuous space actually covered in the original SFLP. In this dissertation I explore this approach and examine factors contributing to solution quality. Three error sources are discussed: point representation spacing, multiple possible solutions to the surrogate point-based model, and round-off errors induced by the computer representation of numbers. Some factors—including boundary region surrogate points and surrogate point location—were also found to make significant contributions to coverage errors. A surrogate error measure using a point-based surrogate model was derived to characterize relationships among spacing, facility coverage area, and spatial coverage error. Locating continuous space facilities with full coverage is important but challenging. Demand surrogate points were initially used as a continuous space for constructing the MIP model, and a point-based surrogate FLP was enhanced for extracting multiple solutions with additional constraints that were found to reduce coverage error. Next, a best initial solution was applied to a proposed heuristic algorithm to serve as an improvement procedure. Algorithm performance was evaluated and applied to a problem involving the location of emergency warning sirens in the city of Dublin, Ohio. The effectiveness of the proposed method for solving this and other facility location/network design problems was demonstrated by comparing the results with those reported in recently published papers.
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Duldig, Paul. "The extent of private health insurance coverage in Australia : public problem or private choice? /." Title page, contents and introduction only, 1985. http://web4.library.adelaide.edu.au/theses/09EC/09ecd881.pdf.

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Silav, Ahmet. "Bi-objective Facility Location Problems In The Presence Of Partial Coverage." Master's thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/2/12610681/index.pdf.

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In this study, we propose a bi-objective facility location model that considers both partial coverage and service to uncovered demands. In this model, it is assumed that the demand nodes within the predefined distance of opened facilities are fully covered and after that distance the coverage level linearly decreases. The objectives are the maximization of the sum of full and partial coverage the minimization of the maximum distance between uncovered demand nodes and their closest opened facilities. We apply two existing Multi Objective Genetic Algorithms (MOGAs), NSGA-II and SPEA-II to the problem. We determine the drawbacks of these MOGAs and develop a new MOGA called modified SPEA-II (mSPEA-II) to avoid the drawbacks. In this method, the fitness function of SPEA-II is modified and the crowding distance calculation of NSGA-II is used. The performance of mSPEA-II is tested on randomly generated problems of different sizes. The results are compared with the solutions resulting from NSGA-II and SPEA-II. Our experiments show that mSPEA-II outperforms both NSGA-II and SPEA-II.
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Books on the topic "Coverage problem"

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Wilk, Marian. Stalin a problem zjednoczenia Niemiec, Gorbaczow --triumf i upadek reformatora, Żyrinowski w ocenie prasy niemieckiej. Łódź: Wyższa Szkoła Studiów Międzynarodowych, 2000.

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United States. Congress. House. Committee on Small Business. The health insurance problem: Alternative strategies to expand coverage among small businesses. Washington: U.S. G.P.O., 1987.

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D, Miethe Terance, ed. Panic: The social construction of the street gang problem. Upper Saddle River, N.J: Prentice Hall, 2002.

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War & press freedom: The problem of prerogative power. New York: Oxford University Press, 1999.

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Media coverage of crime and criminal justice. Durham, N.C: Carolina Academic Press, 2011.

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Media coverage of crime and criminal justice. Durham, North Carolina: Carolina Academic Press, 2014.

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author, Wong Jimmy, ed. The RCIIIS: The endless merry-go-round : the 40-year-old problem of illegal immigrants in Sabah. Kuala Lumpur: DAP Malaysia, 2015.

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Murthy, D. V. R., 1962- author, ed. Social problems and the Indian press. New Delhi: Kanishka Publishers, Distributors, 2014.

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Savkin, Andrey V., Teddy M. Cheng, Zhiyu Xi, Faizan Javed, Alexey S. Matveev, and Hung Nguyen, eds. Decentralized Coverage Control Problems for Mobile Robotic Sensor and Actuator Networks. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2015. http://dx.doi.org/10.1002/9781119058052.

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Llaguno, Marta Martín. La "función de recuerdo" de los medios de difusión: Qué pasa cuando en los medios "parece no pasar nada sobre un tema"? [Alicante]: Universidad de Alicante, 2002.

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Book chapters on the topic "Coverage problem"

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Erzin, Adil, and Natalya Lagutkina. "Barrier Coverage Problem in 2D." In Algorithms for Sensor Systems, 118–30. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-14094-6_8.

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Li, Songhua, Minming Li, Lingjie Duan, and Victor C. S. Lee. "Online Maximum k-Interval Coverage Problem." In Combinatorial Optimization and Applications, 455–70. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-64843-5_31.

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Geunes, Joseph. "Scope of Problem Coverage and Introduction." In SpringerBriefs in Optimization, 3–14. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4419-9347-2_1.

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Li, Deying, Jiannong Cao, Dongsheng Liu, Ying Yu, and Hui Sun. "Algorithms for the m-Coverage Problem and k-Connected m-Coverage Problem in Wireless Sensor Networks." In Lecture Notes in Computer Science, 250–59. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-74784-0_26.

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Singh, Anuj, Rishi Ranjan Singh, and S. R. S. Iyengar. "Hybrid Centrality Measures for Service Coverage Problem." In Computational Data and Social Networks, 81–94. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-34980-6_11.

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Chaudhary, Manju, and Arun K. Pujari. "Q-Coverage Problem in Wireless Sensor Networks." In Distributed Computing and Networking, 325–30. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-92295-7_39.

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Lim, JongBeom, HeonChang Yu, and JoonMin Gil. "Sensor Coverage Problem in Sparse MANET Environments." In Advances in Computer Science and Ubiquitous Computing, 273–78. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-3023-9_44.

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Cellinese, Francesco, Gianlorenzo D’Angelo, Gianpiero Monaco, and Yllka Velaj. "The Multi-budget Maximum Weighted Coverage Problem." In Lecture Notes in Computer Science, 173–86. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-75242-2_12.

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Xu, Jiankang, Xuzhou Shi, Zesheng Zhu, and Hang Gao. "Survey on UAV Coverage Path Planning Problem." In Lecture Notes in Electrical Engineering, 1601–7. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-8411-4_211.

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Ding, Shuxin, Chen Chen, Qi Zhang, Bin Xin, and Panos M. Pardalos. "Stochastic Node Deployment for Area Coverage Problem." In Metaheuristics for Resource Deployment under Uncertainty in Complex Systems, 29–44. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003202653-2.

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Conference papers on the topic "Coverage problem"

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Sturdy, Ian, and Rex Kincaid. "The robust maximum-coverage problem." In 2014 Systems and Information Engineering Design Symposium (SIEDS). IEEE, 2014. http://dx.doi.org/10.1109/sieds.2014.6829904.

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Sheltami, Tarek, Ashraf Mahmoud, Khalid Alafari, and Elhadi Shakshuki. "Self-organizing sensor networks: Coverage problem." In 2012 26th Biennial Symposium on Communications (QBSC). IEEE, 2012. http://dx.doi.org/10.1109/qbsc.2012.6221358.

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Bajaj, Dimple, and Manju. "Maximum coverage heuristics (MCH) for target coverage problem in Wireless Sensor Network." In 2014 IEEE International Advance Computing Conference (IACC). IEEE, 2014. http://dx.doi.org/10.1109/iadcc.2014.6779338.

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Jedda, Ahmed, Mazen G. Khair, and Hussein T. Mouftah. "Distributed algorithms for the RFID coverage problem." In ICC 2013 - 2013 IEEE International Conference on Communications. IEEE, 2013. http://dx.doi.org/10.1109/icc.2013.6654773.

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Hahanov, V. I., E. I. Litvinova, S. V. Chumachenko, Baghdadi Ammar Awni Abbas, and Eshetie Abebech Mandefro. "Qubit model for solving the coverage problem." In 2013 11th East-West Design and Test Symposium (EWDTS). IEEE, 2013. http://dx.doi.org/10.1109/ewdts.2013.6673167.

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Savla, Ketan, Francesco Bullo, and Emilio Frazzoli. "The coverage problem for loitering Dubins vehicles." In 2007 46th IEEE Conference on Decision and Control. IEEE, 2007. http://dx.doi.org/10.1109/cdc.2007.4435017.

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Yoon, Yourim, Yong-Hyuk Kim, and Byung-Ro Moon. "Feasibility-preserving crossover for maximum k-coverage problem." In the 10th annual conference. New York, New York, USA: ACM Press, 2008. http://dx.doi.org/10.1145/1389095.1389209.

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Bays, Matthew J., Apoorva Shende, Daniel J. Stilwell, and Signe A. Redfield. "A solution to the multiple aspect coverage problem." In 2011 IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2011. http://dx.doi.org/10.1109/icra.2011.5980222.

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Bhatta, B. K., and S. K. Jena. "Global t-Sweep Coverage Problem with Minimum Interference." In 2015 International Conference on Information Technology (ICIT). IEEE, 2015. http://dx.doi.org/10.1109/icit.2015.28.

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Magri, Luca, and Andrea Fusiello. "Multiple Models Fitting as a Set Coverage Problem." In 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2016. http://dx.doi.org/10.1109/cvpr.2016.361.

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Reports on the topic "Coverage problem"

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Lo, Shaw-Hwa. From Species Problem to a General Coverage Problem via a New Interpretation. Fort Belvoir, VA: Defense Technical Information Center, March 1989. http://dx.doi.org/10.21236/ada208731.

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Mutch, Patricia. Processing Problems in the IRUS Queries: An Empirical Verification of Problem Coverage in the Natural Language Sourcebook. Fort Belvoir, VA: Defense Technical Information Center, August 1990. http://dx.doi.org/10.21236/ada232780.

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Lo, Shaw-Hwa. General Coverage Problems with Applications, and Bootstrap Method in Survival Analysis and Reliability Theory. Fort Belvoir, VA: Defense Technical Information Center, January 1998. http://dx.doi.org/10.21236/ada337421.

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Sturzenegger, Germán, Cecilia Vidal, and Sebastián Martínez. The Last Mile Challenge of Sewage Services in Latin America and the Caribbean. Edited by Anastasiya Yarygina. Inter-American Development Bank, November 2020. http://dx.doi.org/10.18235/0002878.

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Access to piped sewage in Latin America and the Caribbean (LAC) cities has been on the rise in recent decades. Yet achieving high rates of end-user connection between dwellings and sewage pipelines remains a challenge for water and sanitation utilities. Governments throughout the region are investing millions in increasing access to sewage services but are failing in the last mile. When households do not connect to the sewage system, the full health and social benefits of sanitation investments fail to accrue, and utilities can face lost revenue and higher operating costs. Barriers to connect are diverse, including low willingness to pay for connection costs and/or the associated tariffs, liquidity and credit constrains to cover the cost of upgrades or repairs, information gaps on the benefits of connecting, behavioral obstacles, and collective action failures. In contexts of weak regulation and strong social pressure, utilities typically lack the ability to enforce connection through fines and legal action. This paper explores the scope of the connectivity problem, identifies potential connection barriers, and discusses policy solutions. A research agenda is proposed in support of evidence-based interventions that have the potential to achieve higher effective sanitation coverage more rapidly and cost-effectively in LAC. This research agenda must focus on: i) quantifying the scope of the problem; ii) understanding the barriers that trigger it; and iii) identifying the most cost-effective policy and market-based solutions.
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Mobley, Erin M., Diana J. Moke, Joel Milam, Carol Y. Ochoa, Julia Stal, Nosa Osazuwa, Maria Bolshakova, et al. Disparities and Barriers to Pediatric Cancer Survivorship Care. Agency for Healthcare Research and Quality (AHRQ), March 2021. http://dx.doi.org/10.23970/ahrqepctb39.

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Objectives. Survival rates for pediatric cancer have dramatically increased since the 1970s, and the population of childhood cancer survivors (CCS) exceeds 500,000 in the United States. Cancer during childhood and related treatments lead to long-term health problems, many of which are poorly understood. These problems can be amplified by suboptimal survivorship care. This report provides an overview of the existing evidence and forthcoming research relevant to disparities and barriers for pediatric cancer survivorship care, outlines pending questions, and offers guidance for future research. Data sources. This Technical Brief reviews published peer-reviewed literature, grey literature, and Key Informant interviews to answer five Guiding Questions regarding disparities in the care of pediatric survivors, barriers to cancer survivorship care, proposed strategies, evaluated interventions, and future directions. Review methods. We searched research databases, research registries, and published reviews for ongoing and published studies in CCS to October 2020. We used the authors’ definition of CCS; where not specified, CCS included those diagnosed with any cancer prior to age 21. The grey literature search included relevant professional and nonprofit organizational websites and guideline clearinghouses. Key Informants provided content expertise regarding published and ongoing research, and recommended approaches to fill identified gaps. Results. In total, 110 studies met inclusion criteria. We identified 26 studies that assessed disparities in survivorship care for CCS. Key Informants discussed subgroups of CCS by race or ethnicity, sex, socioeconomic status, and insurance coverage that may experience disparities in survivorship care, and these were supported in the published literature. Key Informants indicated that major barriers to care are providers (e.g., insufficient knowledge), the health system (e.g., availability of services), and payers (e.g., network adequacy); we identified 47 studies that assessed a large range of barriers to survivorship care. Sixteen organizations have outlined strategies to address pediatric survivorship care. Our searches identified only 27 published studies that evaluated interventions to alleviate disparities and reduce barriers to care. These predominantly assessed approaches that targeted patients. We found only eight ongoing studies that evaluated strategies to address disparities and barriers. Conclusions. While research has addressed disparities and barriers to survivorship care for childhood cancer survivors, evidence-based interventions to address these disparities and barriers to care are sparse. Additional research is also needed to examine less frequently studied disparities and barriers and to evaluate ameliorative strategies in order to improve the survivorship care for CCS.
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Führ, Martin, Julian Schenten, and Silke Kleihauer. Integrating "Green Chemistry" into the Regulatory Framework of European Chemicals Policy. Sonderforschungsgruppe Institutionenanalyse, July 2019. http://dx.doi.org/10.46850/sofia.9783941627727.

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20 years ago a concept of “Green Chemistry” was formulated by Paul Anastas and John Warner, aiming at an ambitious agenda to “green” chemical products and processes. Today the concept, laid down in a set of 12 principles, has found support in various arenas. This diffusion was supported by enhancements of the legislative framework; not only in the European Union. Nevertheless industry actors – whilst generally supporting the idea – still see “cost and perception remain barriers to green chemistry uptake”. Thus, the questions arise how additional incentives as well as measures to address the barriers and impediments can be provided. An analysis addressing these questions has to take into account the institutional context for the relevant actors involved in the issue. And it has to reflect the problem perception of the different stakeholders. The supply chain into which the chemicals are distributed are of pivotal importance since they create the demand pull for chemicals designed in accordance with the “Green Chemistry Principles”. Consequently, the scope of this study includes all stages in a chemical’s life-cycle, including the process of designing and producing the final products to which chemical substances contribute. For each stage the most relevant legislative acts, together establishing the regulatory framework of the “chemicals policy” in the EU are analysed. In a nutshell the main elements of the study can be summarized as follows: Green Chemistry (GC) is the utilisation of a set of principles that reduces or eliminates the use or generation of hazardous substances in the design, manufacture and application of chemical products. Besides, reaction efficiency, including energy efficiency, and the use of renewable resources are other motives of Green Chemistry. Putting the GC concept in a broader market context, however, it can only prevail if in the perception of the relevant actors it is linked to tangible business cases. Therefore, the study analyses the product context in which chemistry is to be applied, as well as the substance’s entire life-cycle – in other words, the six stages in product innovation processes): 1. Substance design, 2. Production process, 3. Interaction in the supply chain, 4. Product design, 5. Use phase and 6. After use phase of the product (towards a “circular economy”). The report presents an overview to what extent the existing framework, i.e. legislation and the wider institutional context along the six stages, is setting incentives for actors to adequately address problematic substances and their potential impacts, including the learning processes intended to invoke creativity of various actors to solve challenges posed by these substances. In this respect, measured against the GC and Learning Process assessment criteria, the study identified shortcomings (“delta”) at each stage of product innovation. Some criteria are covered by the regulatory framework and to a relevant extent implemented by the actors. With respect to those criteria, there is thus no priority need for further action. Other criteria are only to a certain degree covered by the regulatory framework, due to various and often interlinked reasons. For those criteria, entry points for options to strengthen or further nuance coverage of the respective principle already exist. Most relevant are the deltas with regard to those instruments that influence the design phase; both for the chemical substance as such and for the end-product containing the substance. Due to the multi-tier supply chains, provisions fostering information, communication and cooperation of the various actors are crucial to underpin the learning processes towards the GCP. The policy options aim to tackle these shortcomings in the context of the respective stage in order to support those actors who are willing to change their attitude and their business decisions towards GC. The findings are in general coherence with the strategies to foster GC identified by the Green Chemistry & Commerce Council.
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Inference in a class of optimization problems: confidence regions and finite sample bounds on errors in coverage probabilities. Cemmap, September 2020. http://dx.doi.org/10.47004/10.47004/wp.cem.2020.4820.

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Inference in a class of optimization problems: confidence regions and finite sample bounds on errors in coverage probabilities. Cemmap, September 2020. http://dx.doi.org/10.47004/wp.cem.2020.4820.

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Inference in a class of optimization problems: Confidence regions and finite sample bounds on errors in coverage probabilities. Cemmap, August 2021. http://dx.doi.org/10.47004/wp.cem.2021.3321.

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