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Journal articles on the topic 'Allocation block'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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1

MARION-POTY, VIRGINIE, and SERGE MIGUET. "DATA ALLOCATION STRATEGIES FOR PARALLEL IMAGE PROCESSING ALGORITHMS." International Journal of Pattern Recognition and Artificial Intelligence 09, no. 04 (1995): 615–34. http://dx.doi.org/10.1142/s0218001495000237.

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This paper discusses several data allocation strategies used for the parallel implementation of basic imaging operators. It shows that depending on the operator (sequential or parallel, with regular or irregular execution time), the image data must be partitioned in very different manners: The square sub-domains are best adapted for minimizing the communication volume, but rectangles can perform better when we take into account the time for constructing messages. Block allocations are well adapted for inherently parallel operators since they minimize interprocessor interactions, but in the cas

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2

Al-kahtani, Mohammed S., Lilatul Ferdouse, and Lutful Karim. "Energy Efficient Power Domain Non-Orthogonal Multiple Access Based Cellular Device-to-Device Communication for 5G Networks." Electronics 9, no. 2 (2020): 237. http://dx.doi.org/10.3390/electronics9020237.

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This paper examines the resource block and power allocation in the power domain non-orthogonal multiple access (PD-NOMA) based cellular device-to-device (D2D) systems. To improve the energy efficiency of the D2D systems and to manage the mutual interference level as well as the quality of service (QoS) requirement of cellular users, different power level is applied to the D2D users sharing the same resource blocks (RBs) to the legacy users. It is essential to design an efficient resource block and power allocation method for PD-NOMA based cellular D2D systems which guarantee the successive int

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3

Došlić, Tomislav. "Block allocation of a sequential resource." Ars Mathematica Contemporanea 17, no. 1 (2019): 79–88. http://dx.doi.org/10.26493/1855-3974.1508.f8c.

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4

Sedgwick, P. "Treatment allocation in trials: block randomisation." BMJ 348, mar28 1 (2014): g2409. http://dx.doi.org/10.1136/bmj.g2409.

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5

LAWAL, NAJEEM, BENNY THÖRNBERG, MATTIAS O'NILS, and HÅKAN NORELL. "RAM ALLOCATION ALGORITHM FOR VIDEO PROCESSING APPLICATIONS ON FPGA." Journal of Circuits, Systems and Computers 15, no. 05 (2006): 679–99. http://dx.doi.org/10.1142/s0218126606003295.

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This paper presents an algorithm for the allocation of on-chip FPGA Block RAMs for the implementation of Real-Time Video Processing Systems. The effectiveness of the algorithm is shown through the implementation of realistic image processing systems. The algorithm, which is based on a heuristic, seeks the most cost-effective way of allocating memory objects to the FPGA Block RAMs. The experimental results obtained, show that this algorithm generates results which are close to the theoretical optimum for most design cases.

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Nguyen, Quang Hong, Khanh Quoc Dinh, Viet Anh Nguyena, Chien Van Trinh, Younghyeon Park, and Byeungwoo Jeon. "Rate Allocation for Block-based Compressive Sensing." Journal of Broadcast Engineering 20, no. 3 (2015): 398–407. http://dx.doi.org/10.5909/jbe.2015.20.3.398.

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7

Bystrom, M., and R. A. Coury. "Rate allocation for serial concatenated block codes." IEEE Transactions on Wireless Communications 4, no. 3 (2005): 830–34. http://dx.doi.org/10.1109/twc.2005.847002.

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8

Salama, Ibrahim, Anastasia Ivanova, and Bahjat Qaqish. "Efficient generation of constrained block allocation sequences." Statistics in Medicine 27, no. 9 (2007): 1421–28. http://dx.doi.org/10.1002/sim.3014.

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9

Xu, Jin, Pei-Ning Guo, and Chung-Kuan Cheng. "Empirical Study of Block Placement by Cluster Refinement." VLSI Design 10, no. 1 (1999): 71–86. http://dx.doi.org/10.1155/1999/89835.

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In this paper we propose an efficient cluster refinement approach for macro-cell placement. The algorithm selects a cluster of blocks dynamically, and finds an optimal solution for all the blocks in the cluster simultaneously. This is different from previous zone refinement approach which optimizes the allocation of one single block in each operation. Experimental results on the MCNC benchmark circuits show that the approach achieves excellent area utilization while minimizing the wire length at the same time.

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10

Patel, Jigisha N., Suprav Patnaik, and Saraiya Mansi. "Block Classification and Transmission of Compressed Image with Bit Allocation and Unequal Error Protection." International Journal of Computer Theory and Engineering 8, no. 4 (2016): 350–54. http://dx.doi.org/10.7763/ijcte.2016.v8.1070.

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11

Sundar Rajan, Arun Kumar, Shriram K. Vasudevan, and Nirmala Devi M. "Trends In Task Allocation For Multicore System." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 6 (2016): 3018. http://dx.doi.org/10.11591/ijece.v6i6.10140.

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<p>As the functionality in real-time embedded systems becoming complex, there has been a demand for higher computation capability, exploitation of parallelism and effective usage of the resources. Further, technological limitations in uniprocessor in terms of power consumption, instruction level parallelism reaching saturation, delay in access of memory blocks; directed towards emergence of multicore. Multicore design has its challenges as well. Increase in number cores has raised the demand for proper load distribution, parallelizing existing sequential codes, enabling effective communi

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12

Sundar Rajan, Arun Kumar, Shriram K. Vasudevan, and Nirmala Devi M. "Trends In Task Allocation For Multicore System." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 6 (2016): 3018. http://dx.doi.org/10.11591/ijece.v6i6.pp3018-3030.

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<p>As the functionality in real-time embedded systems becoming complex, there has been a demand for higher computation capability, exploitation of parallelism and effective usage of the resources. Further, technological limitations in uniprocessor in terms of power consumption, instruction level parallelism reaching saturation, delay in access of memory blocks; directed towards emergence of multicore. Multicore design has its challenges as well. Increase in number cores has raised the demand for proper load distribution, parallelizing existing sequential codes, enabling effective communi

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13

Fan, Jiancun, Qinye Yin, Geoffrey Ye Li, Bingguang Peng, and Xiaolong Zhu. "Adaptive Block-Level Resource Allocation in OFDMA Networks." IEEE Transactions on Wireless Communications 10, no. 11 (2011): 3966–72. http://dx.doi.org/10.1109/twc.2011.092011.110624.

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14

Bistritz, Ilai, and Amir Leshem. "Asymptotically Optimal Resource Block Allocation With Limited Feedback." IEEE Transactions on Wireless Communications 18, no. 1 (2019): 34–46. http://dx.doi.org/10.1109/twc.2018.2875706.

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15

Zhang, Jie, Pingping Sun, Feng Zhao, Qianru Guo, and Yue Zou. "Network Pseudohealth Information Recognition Model: An Integrated Architecture of Latent Dirichlet Allocation and Data Block Update." Complexity 2020 (December 21, 2020): 1–12. http://dx.doi.org/10.1155/2020/6612043.

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The wanton dissemination of network pseudohealth information has brought great harm to people’s health, life, and property. It is important to detect and identify network pseudohealth information. Based on this, this paper defines the concepts of pseudohealth information, data block, and data block integration, designs an architecture that combines the latent Dirichlet allocation (LDA) algorithm and data block update integration, and proposes the combination algorithm model. In addition, crawler technology is used to crawl the pseudohealth information transmitted on the Sina Weibo platform dur

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16

Deng, Hongyu, Cheng Wu, and Yiming Wang. "A cognitive gateway-based spectrum sharing method in downlink round robin scheduling of LTE system." Modern Physics Letters B 31, no. 19-21 (2017): 1740070. http://dx.doi.org/10.1142/s021798491740070x.

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A key technique of LTE is how to allocate efficiently the resource of radio spectrum. Traditional Round Robin (RR) scheduling scheme may lead to too many resource residues when allocating resources. When the number of users in the current transmission time interval (TTI) is not the greatest common divisor of resource block groups (RBGs), and such a phenomenon lasts for a long time, the spectrum utilization would be greatly decreased. In this paper, a novel spectrum allocation scheme of cognitive gateway (CG) was proposed, in which the LTE spectrum utilization and CG’s throughput were greatly i

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17

Berger, Vance W. "Varying the block size does not conceal the allocation." Journal of Critical Care 21, no. 2 (2006): 229. http://dx.doi.org/10.1016/j.jcrc.2006.01.002.

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18

Nguyen, Khoa D., Albert Guillen i Fabregas, and Lars K. Rasmussen. "Outage Exponents of Block-Fading Channels With Power Allocation." IEEE Transactions on Information Theory 56, no. 5 (2010): 2373–81. http://dx.doi.org/10.1109/tit.2010.2043768.

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19

Hwang, InHyuck, SeungHoon Nam, and JongGye Shin. "An Automatic Block Allocation Methodology at Shipbuilding Midterm Scheduling." Transactions of the Society of CAD/CAM Engineers 17, no. 6 (2012): 409–16. http://dx.doi.org/10.7315/cadcam.2012.409.

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20

Apling, Richard N., and Christine Padilla. "Funds Allocation and Expenditures Under the Education Block Grant." Educational Evaluation and Policy Analysis 8, no. 4 (1986): 403–22. http://dx.doi.org/10.3102/01623737008004403.

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21

Wang, Yu, Yu Zhang, and Jiafu Tang. "A distributionally robust optimization approach for surgery block allocation." European Journal of Operational Research 273, no. 2 (2019): 740–53. http://dx.doi.org/10.1016/j.ejor.2018.08.037.

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22

Cho, KyungWoon, and Hyokyung Bahn. "Performance Analysis of Thread Block Schedulers in GPGPU and Its Implications." Applied Sciences 10, no. 24 (2020): 9121. http://dx.doi.org/10.3390/app10249121.

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GPGPU (General-Purpose Graphics Processing Unit) consists of hardware resources that can execute tens of thousands of threads simultaneously. However, in reality, the parallelism is limited as resource allocation is performed by the base unit called thread block, which is not managed judiciously in the current GPGPU systems. To schedule threads in GPGPU, a specialized hardware scheduler allocates thread blocks to the computing unit called SM (Stream Multiprocessors) in a Round-Robin manner. Although scheduling in hardware is simple and fast, we observe that the Round-Robin scheduling is not ef

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23

Chorti, Arsenia, Katerina Papadaki, and H. Vincent Poor. "Optimal Power Allocation in Block Fading Channels With Confidential Messages." IEEE Transactions on Wireless Communications 14, no. 9 (2015): 4708–19. http://dx.doi.org/10.1109/twc.2015.2424964.

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24

Zhang, Lu, and Leonard J. Cimini. "Efficient power allocation for decentralized distributed space-time block coding." IEEE Transactions on Wireless Communications 8, no. 3 (2009): 1102–6. http://dx.doi.org/10.1109/twc.2009.080153.

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25

Nguyen, Khoa, Albert I Fabregas, and Lars Rasmussen. "Power allocation for block-fading channels with arbitrary input constellations." IEEE Transactions on Wireless Communications 8, no. 5 (2009): 2514–23. http://dx.doi.org/10.1109/twc.2009.080248.

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26

Lee, Jong-Chan, and Moon-Ho Lee. "Service Block Based Resource Allocation Scheme for Macrocell-Femtocell Networks." Journal of the Korea Society of Computer and Information 20, no. 6 (2015): 29–35. http://dx.doi.org/10.9708/jksci.2015.20.6.029.

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27

Zenteno, Ana Cecilia, Tim Carnes, Retsef Levi, Bethany J. Daily, and Peter F. Dunn. "Systematic OR Block Allocation at a Large Academic Medical Center." Annals of Surgery 264, no. 6 (2016): 973–81. http://dx.doi.org/10.1097/sla.0000000000001560.

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28

Chao, Xu, He Yan-xiang, Chen Yong, Wu Wei, and Zeng Xiao-ling. "An Optimization Algorithm of Variable Allocation Based on Block Architecture." Applied Mathematics & Information Sciences 7, no. 2 (2013): 691–99. http://dx.doi.org/10.12785/amis/070237.

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29

Welder, Matthew D., Keith A. Warhurst, Wesley J. L. Anderson, et al. "Service Block Time Allocation in the US Army Medical Command." AORN Journal 104, no. 5 (2016): 417–25. http://dx.doi.org/10.1016/j.aorn.2016.09.003.

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30

Li, Ting. "The Effects of RB Usage on Single User Rate in TD-LTE." Advanced Materials Research 981 (July 2014): 478–81. http://dx.doi.org/10.4028/www.scientific.net/amr.981.478.

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Resource Block (RB) allocation effects network coverage and throughput. The impact principles are analyzed in theory. Exist TD-LTE network data is collected, organized and analyzed. The results show that the effects of RB allocation on user rate in downlink is greater than uplink and uplink RB usage is more stable.

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31

Wang, Ying, Xiang Guo, Yueyan Zhu, and Jianqiao Zhang. "Color Block Task." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 60, no. 1 (2016): 1889–93. http://dx.doi.org/10.1177/1541931213601430.

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With the increasing use of in-vehicle information system (IVIS), driver distraction, especially visual distraction, has increased dramatically. Evaluating the impact of IVIS on traffic safety is important. Previous studies have used various standard secondary-task methods in place of real IVIS interactions to obtain quantitative and scalable results. However, traditional visual secondary tasks, such as the Surrogate Reference Task (SuRT) and the Arrow Task, are insufficient to simulate incrementally increased workload with fine details or contrast difference. This study designed a new form of

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32

Keen, Leigh, Jenna Bulger, Nigel Rees, et al. "03 The use of scratchcards for allocation concealment and treatment allocation in a prehospital randomised controlled trial." Emergency Medicine Journal 36, no. 1 (2019): e2.1-e2. http://dx.doi.org/10.1136/emermed-2019-999.3.

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BackgroundRAPID (Rapid Analgesia for Prehospital Hip Disruption) study was a small study to determine the feasibility of undertaking a randomised controlled trial to test the clinical and cost-effectiveness of paramedics administering Fascia Iliaca Compartment Block (FICB) as early pain relief to patients who have fractured a hip at the scene of their injury.ObjectivesTo devise a simple and effective method of random allocation concealment suitable for use by Paramedics whilst in the mobile emergency prehospital setting.MethodsTraditional Methods of randomly allocating patients were considered

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33

Danisya, Achmad Rizal, Rendy Munadi, and Sofia Naning Hertiana. "Analysis Of User Throughput Based Predictive Mobility Load Balancing Using Logarithmic Regression Of Reference Signal Received Quality In Long Term Evolution Radio Access Network." JURNAL INFOTEL 10, no. 1 (2018): 1. http://dx.doi.org/10.20895/infotel.v10i1.350.

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The improvement of Long Term Evolution (LTE) radio access network services is affecting the increased value of traffic load in its network, which is causing traffic unbalance between cells in LTE Radio Access Network (RAN). Users will be served with ineffective resource block allocation which will make the total of gained throughput are not optimal. A method is required to move network load from overloaded cells to underloaded cells in order to balance the resource block allocation optimally. By using NS-3.26 simulation, User Throughput Based (UTB) predictive Mobility Load Balancing (MLB) meth

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34

Xie Chen, Gong Shengrong, Liu Chunping, and Ji Yi. "Adaptive Block-level Measurements Allocation Landweber Reconstruction based on Dictionary Learning." International Journal of Advancements in Computing Technology 5, no. 6 (2013): 364–72. http://dx.doi.org/10.4156/ijact.vol5.issue6.43.

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35

Okumoto, Yasuhisa, and Ryutaro Iseki. "Optimization of Block Allocation in Assembly Area Using Simulated Annealing Method." Journal of the Japan Society of Naval Architects and Ocean Engineers 1 (2005): 71–76. http://dx.doi.org/10.2534/jjasnaoe.1.71.

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36

Pischella, Mylene, Rostom Zakaria, and Didier Le Ruyet. "Resource Block-Level Power Allocation in Asynchronous Multi-Carrier D2D Communications." IEEE Communications Letters 21, no. 4 (2017): 813–16. http://dx.doi.org/10.1109/lcomm.2016.2640273.

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37

Burdett, R., E. Kozan, and R. Kenley. "Block models for improved earthwork allocation planning in linear infrastructure construction." Engineering Optimization 47, no. 3 (2014): 347–69. http://dx.doi.org/10.1080/0305215x.2014.892594.

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38

Nugraha, Toha Ardi, Indar Surahmat, and Firdaus Firdaus. "Block diagonalization precoding and power allocation for clustering small-cell networks." Bulletin of Electrical Engineering and Informatics 9, no. 6 (2020): 2364–70. http://dx.doi.org/10.11591/eei.v9i6.2580.

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The clustering network is a solution to improve data-rate transmission in small-cells. In this case, clustering small-cells (CSCs) adopt a multiple antennas concept. The multiple antennas are used to maximize the downlink data-rate transmission at the users, but it requires precoding techniques to minimize interference among CSC users. This paper proposes a block diagonalization (BD) as a precoding technique for minimizing interference among CSC users. The performance of the BD precoding implemented on the clustering network under various numbers of small-cells. The CSC also implements a water

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39

Wang, Chih-Yu, Hung-Yu Wei, and Wen-Tsuen Chen. "Resource Block Allocation with Carrier-Aggregation: A Strategy-Proof Auction Design." IEEE Transactions on Mobile Computing 15, no. 12 (2016): 3142–55. http://dx.doi.org/10.1109/tmc.2016.2524633.

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40

Gandotra, Pimmy, and Rakesh Kumar Jha. "Energy-efficient device-to-device communication using adaptive resource-block allocation." International Journal of Communication Systems 32, no. 8 (2019): e3922. http://dx.doi.org/10.1002/dac.3922.

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41

Hin Wong, Wing, and E. G. Larsson. "Orthogonal space-time block coding with antenna selection and power allocation." Electronics Letters 39, no. 4 (2003): 379. http://dx.doi.org/10.1049/el:20030253.

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42

Nwamadi, O., A. K. Nandi, and X. Zhu. "Dynamic physical resource block allocation algorithms for uplink long term evolution." IET Communications 5, no. 7 (2011): 1020–27. http://dx.doi.org/10.1049/iet-com.2010.0316.

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43

de Haan, J. E. S., M. Gibescu, D. A. M. Klaar, and W. L. Kling. "Sizing and allocation of frequency restoration reserves for LFC Block cooperation." Electric Power Systems Research 128 (November 2015): 60–65. http://dx.doi.org/10.1016/j.epsr.2015.06.020.

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44

Abdullah, Shapina, Norashidah Md Din, Shamsul J. Elias, Adam Wong Yoon Khang, Roshidi Din, and Rosmadi Bakar. "Design of a cell selection mechanism to mitigate interference for cell-edge macro users in femto-macro heterogeneous network." Bulletin of Electrical Engineering and Informatics 8, no. 1 (2019): 180–87. http://dx.doi.org/10.11591/eei.v8i1.1433.

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The Femto-Macro heterogeneous network is a promising solution to improve the network capacity and coverage in mobile network. However interference may rise due to femtocell deployment nearby to macro user equipment (MUE) within macrocell network coverage. Femtocell offers main priority in resource allocation to its subscribed femto user equipment (FUE) rather than unsubscribed MUE. MUEs will suffer severe interference when they are placed near or within the femtocell area range especially at the cell edge. This phenomenon occurs due to the distance is far from its serving macro base station (M

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45

Samčović, Andreja. "Analysis of Coding Gain and Optimal Bit Allocation in Motion-Compensated Video Compression." Journal of Electrical Engineering 63, no. 2 (2012): 129–32. http://dx.doi.org/10.2478/v10187-012-0020-z.

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Analysis of Coding Gain and Optimal Bit Allocation in Motion-Compensated Video CompressionThis paper describes mathematical frameworks on temporal and spatial predictive processing in the motion-compensated video compression. Firstly, the coding gain over intra coding is derived, regarding the bit allocation algorithm and Lagrange multiplier method. The optimal ordering of three different picture types (I, P and B pictures) is clarified according to image source characteristics. Secondly, a novel framework with the block-based multihypothesis motion-compensated optimal coding gain and bit allo

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46

Geary, Elizabeth M., Martin Goldberg, A. G. Greenburg, and Thomas E. Johnson. "Predicting operating room case load: An aid to resource allocation." Journal of Hospital Administration 2, no. 4 (2013): 151. http://dx.doi.org/10.5430/jha.v2n4p151.

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Hospital patient bed utilization can reach 100% with an impact on elective surgery schedules. Analysis of the demand for beds created by elective surgical operations is desirable to manage overall resources under these conditions. For planning and allocating operating rooms, staff, beds and equipment on any given day, hospital administrators would benefit from an accurate prediction of the number of surgical cases that will be completed. Current scheduling techniques do not predict, for a given day in the future, the number of cases that will actually be performed. A study was performed at a 2

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47

Makarov, Vladimir, Mikhail Guzev, and Vladimir Odintsev. "About the base problems of the geomechanics of strong compressed rock and rock masses." E3S Web of Conferences 192 (2020): 01002. http://dx.doi.org/10.1051/e3sconf/202019201002.

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Some approaches to the simulation of hierarchically-block geomedia are considered. The idea of mesomechanics with allocation of mesovolume of representative scale level is used. It is offered to describe within the frame of geomechanics a rock mass four scale levels considering the conforming hierarchy of structural blocks. On each of these levels the rock mass is presented by non-Euclidian model of a continuous medium with the cracking defects, thus models of different scale levels differ only with values of parametres entering into them.

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48

SU, XIAO, and BENJAMIN W. WAH. "LOSS AWARE RATE ALLOCATIONS IN H.263 CODED VIDEO TRANSMISSIONS." Journal of Circuits, Systems and Computers 14, no. 06 (2005): 1157–71. http://dx.doi.org/10.1142/s0218126605002878.

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For packet video, information loss and bandwidth limitation are two factors that affect video playback quality. Traditional rate allocation approaches have focused on optimizing video quality under bandwidth constraint alone. However, in the best-effort Internet, packets carrying video data are susceptible to losses, which need to be reconstructed at the receiver side. In this paper, we propose loss aware rate allocations in both group-of-block (GOB) level and macroblock level, given that certain packets are lost during transmissions and reconstructed using simple interpolation methods at the

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49

CORNER, J. L., and L. R. FOULDS. "SCHEDULING THE HARVESTING OPERATIONS OF A FOREST BLOCK: A CASE STUDY." Asia-Pacific Journal of Operational Research 22, no. 03 (2005): 377–90. http://dx.doi.org/10.1142/s0217595905000674.

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We discuss the harvesting of a single forest block from an operations scheduling viewpoint. We report on a harvesting case study, based on practical data from a commercial enterprise, involving minimum and maximum time lags and resource constraints. It appears that the scheduling of the harvesting forest blocks is a significantly different scenario from those represented by the scheduling models available in the literature. The differences come about because: the duration of each operation is dependent upon the combination of constrained resources allocated to it, individual worker-equipment a

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50

Balocco, Angela Lucia, Ana M. López, Cedric Kesteloot, et al. "Quadratus lumborum block: an imaging study of three approaches." Regional Anesthesia & Pain Medicine 46, no. 1 (2020): 35–40. http://dx.doi.org/10.1136/rapm-2020-101554.

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Background and objectivesDifferent injection techniques for the quadratus lumborum (QL) block have been described. Data in human cadavers suggest that the transverse oblique paramedian (TOP) QL3 may reach the thoracic paravertebral space more consistently than the QL1 and QL2. However, the distribution of injectate in cadavers may differ from that in patients. Hence, we assessed the distribution of the injectate after the QL1, QL2, and TOP QL3 techniques in patients.Materials and methodsThirty-four patients scheduled for abdominal surgery received QL blocks postoperatively; 26 patients receive

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