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Artículos de revistas sobre el tema "Source enumeration"

Autor: Grafiati
Publicado: 21 de diciembre de 2024

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1

Lee, Yunseong, Chanhong Park, Taeyoung Kim, et al. "Source Enumeration Approaches Using Eigenvalue Gaps and Machine Learning Based Threshold for Direction-of-Arrival Estimation." Applied Sciences 11, no. 4 (2021): 1942. http://dx.doi.org/10.3390/app11041942.

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Source enumeration is an important procedure for radio direction-of-arrival finding in the multiple signal classification (MUSIC) algorithm. The most widely used source enumeration approaches are based on the eigenvalues themselves of the covariance matrix obtained from the received signal. However, they have shortcomings such as the imperfect accuracy even at a high signal-to-noise ratio (SNR), the poor performance at low SNR, and the limited detection number of sources. This paper proposestwo source enumeration approaches using the ratio of eigenvalue gaps and the threshold trained by a mach
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2

Kim, Taeyoung, Yunseong Lee, Chanhong Park, et al. "Source Enumeration Method using Eigenvalue Gap Ratio and Performance Comparison in Rayleigh Fading." Journal of the Korea Institute of Military Science and Technology 24, no. 5 (2021): 492–502. http://dx.doi.org/10.9766/kimst.2021.24.5.492.

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In electronic warfare, source enumeration and direction-of-arrival estimation are important. The source enumeration method based on eigenvalues of covariance matrix from received is one of the most used methods. However, there are some drawbacks such as accuracy less than 100 % at high SNR, poor performance at low SNR and reduction of maximum number of estimating sources. We suggested new method based on eigenvalues gaps, which is named AREG(Accumulated Ratio of Eigenvalues Gaps). Meanwhile, FGML(Fast Gridless Maximum Likelihood) which reconstructs the covariance matrix was suggested by Wu et
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3

Cuichun Xu and S. Kay. "Source Enumeration via the EEF Criterion." IEEE Signal Processing Letters 15 (2008): 569–72. http://dx.doi.org/10.1109/lsp.2008.2001112.

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4

Ge, Shengguo, Siti Nurulain Mohd Rum, Hamidah Ibrahim, Erzam Marsilah, and Thinagaran Perumal. "A Source Number Enumeration Method at Low SNR Based on Ensemble Learning." International Journal of Emerging Technology and Advanced Engineering 13, no. 3 (2023): 81–90. http://dx.doi.org/10.46338/ijetae0323_08.

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Source number estimation is one of the important research directions in array signal processing. To solve the difficulty of estimating the number of signal sources under a low signal-to-noise ratio (SNR), a source number enumeration method based on ensemble learning is proposed. This method first preprocesses the signal data. The specific process is to decompose the original signal into several intrinsic mode functions (IMF) by using Complementary Ensemble Empirical Mode Decomposition (CEEMD), and then construct a covariance matrix and perform eigenvalue decomposition to obtain samples. Finall
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5

Loyer, P., J. M. Moureaux, and M. Antonini. "Lattice codebook enumeration for generalized Gaussian source." IEEE Transactions on Information Theory 49, no. 2 (2003): 521–27. http://dx.doi.org/10.1109/tit.2002.807306.

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6

Cozzens, J. H., and M. J. Sousa. "Source enumeration in a correlated signal environment." IEEE Transactions on Signal Processing 42, no. 2 (1994): 304–17. http://dx.doi.org/10.1109/78.275604.

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7

Akeroyd, Michael A., William M. Whitmer, David McShefferty, and Graham Naylor. "Sound-source enumeration by hearing-impaired adults." Journal of the Acoustical Society of America 139, no. 4 (2016): 2210. http://dx.doi.org/10.1121/1.4950605.

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8

Diaz-Santos, Jose A., and Kathleen E. Wage. "Whitening and source enumeration for large underwater arrays." Journal of the Acoustical Society of America 148, no. 4 (2020): 2477. http://dx.doi.org/10.1121/1.5146862.

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9

Garg, Vaibhav, Ignacio Santamaria, David Ramirez, and Louis L. Scharf. "Subspace Averaging and Order Determination for Source Enumeration." IEEE Transactions on Signal Processing 67, no. 11 (2019): 3028–41. http://dx.doi.org/10.1109/tsp.2019.2912151.

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10

Eguizabal, Alma, Christian Lameiro, David Ramirez, and Peter J. Schreier. "Source Enumeration in the Presence of Colored Noise." IEEE Signal Processing Letters 26, no. 3 (2019): 475–79. http://dx.doi.org/10.1109/lsp.2019.2895548.

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11

Lei Huang and Shunjun Wu. "Low-Complexity MDL Method for Accurate Source Enumeration." IEEE Signal Processing Letters 14, no. 9 (2007): 581–84. http://dx.doi.org/10.1109/lsp.2006.885286.

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12

Xiang, Ning, and Thomas Metzger. "Prediction model formulations for detection, enumeration, and localization of multiple sound sources using spherical harmonics." Journal of the Acoustical Society of America 151, no. 4 (2022): A231. http://dx.doi.org/10.1121/10.0011157.

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A spherical microphone array is used to detect and localize sound sources in terms of model-based machine learning (ML). In this application, it is crucial to establish parametric models to distinguish background sound environment from presence of sound sources. In the presence of sound sources, the parameter models are also used to localize an unknown number of potentially multiple sound sources. In this work, a model-based Bayesian learning framework is presented for localizing an unknown number of sound sources. Among them, a no-source scenario needs to be accounted for. The model-based mac
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13

Ke, Xiaochuan, Yuan Zhao, and Lei Huang. "On Accurate Source Enumeration: A New Bayesian Information Criterion." IEEE Transactions on Signal Processing 69 (2021): 1012–27. http://dx.doi.org/10.1109/tsp.2021.3052052.

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14

Fan, Rong, Xinyu Zhu, Wenbo Tang, and Chengke Si. "MFFNet: Multi-Path Features Fusion Network for Source Enumeration." IEEE Communications Letters 26, no. 3 (2022): 572–76. http://dx.doi.org/10.1109/lcomm.2021.3139676.

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15

Ge, Shengguo, Siti Nurulain Binti Mohd Rum, Hamidah Ibrahim, Erzam Marsilah, and Thinagaran Perumal. "An Effective Source Number Enumeration Approach Based on SEMD." IEEE Access 10 (2022): 96066–78. http://dx.doi.org/10.1109/access.2022.3204998.

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16

Lu, Zhihua, and Abdelhak M. Zoubir. "Flexible Detection Criterion for Source Enumeration in Array Processing." IEEE Transactions on Signal Processing 61, no. 6 (2013): 1303–14. http://dx.doi.org/10.1109/tsp.2012.2234747.

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17

Luan, Luan, Chunxiang Gu, Yonghui Zheng, and Yanan Shi. "Lattice Enumeration with Discrete Pruning: Improvements, Cost Estimation and Optimal Parameters." Mathematics 11, no. 3 (2023): 766. http://dx.doi.org/10.3390/math11030766.

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Lattice enumeration is a linear-space algorithm for solving the shortest lattice vector problem (SVP). Extreme pruning is a practical technique for accelerating lattice enumeration, which has a mature theoretical analysis and practical implementation. However, these works have yet to be applied to discrete pruning. In this paper, we improve the discrete pruned enumeration (DP enumeration) and provide a solution to the problem proposed by Léo Ducas and Damien Stehlé regarding the cost estimation of discrete pruning. We first rectify the randomness assumption to more precisely describe the latti
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18

Ginsberg, Caren A. "Estimates and Correlates of Enumeration Completeness: Censuses and Maps in Nineteenth-Century Massachusetts." Social Science History 12, no. 1 (1988): 71–86. http://dx.doi.org/10.1017/s0145553200016023.

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Data quality is a central analytical issue in most studies of historical populations. There is often a need for data correction as well as for a careful consideration of the sources and types of error in data collection. Cross-identification of enumerated or registered events in independent sources often can be used as a check on data quality. This study investigates data quality of two sources by their enumeration comparability and in addition discusses some of the problems with such a comparison. The two sources compared are household listings of the United States manuscript federal censuses
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19

Li, Congduan, Steven Weber, and John MacLaren Walsh. "On Multi-Source Networks: Enumeration, Rate Region Computation, and Hierarchy." IEEE Transactions on Information Theory 63, no. 11 (2017): 7283–303. http://dx.doi.org/10.1109/tit.2017.2745620.

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20

Haddadi, Farzan, Mohammadreza Malek-Mohammadi, Mohammad Mahdi Nayebi, and Mohammad R. Aref. "Statistical Performance Analysis of MDL Source Enumeration in Array Processing." IEEE Transactions on Signal Processing 58, no. 1 (2010): 452–57. http://dx.doi.org/10.1109/tsp.2009.2028207.

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21

Lu, Zhihua, and Abdelhak M. Zoubir. "Generalized Bayesian Information Criterion for Source Enumeration in Array Processing." IEEE Transactions on Signal Processing 61, no. 6 (2013): 1470–80. http://dx.doi.org/10.1109/tsp.2012.2232661.

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22

Lu, Zhihua, and Abdelhak M. Zoubir. "Source Enumeration in Array Processing Using a Two-Step Test." IEEE Transactions on Signal Processing 63, no. 10 (2015): 2718–27. http://dx.doi.org/10.1109/tsp.2015.2414894.

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23

Yareshchenko, Vladyslav, and Viktor Kosenko. "UNIT-DISTANCE CODES ENUMERATION." Advanced Information Systems 8, no. 4 (2024): 41–48. http://dx.doi.org/10.20998/2522-9052.2024.4.06.

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The article discusses the current problem of reducing power dissipation in global communication lines while maintaining high performance. With the increasing complexity of system on chip, power consumption has become a major issue in system design. The main source of dynamic power dissipation in digital circuits is buses. Bus switching activity accounts for a significant portion of the total power dissipation. One effective method for reducing switching activity during device-to-device or on-chip communication is the use of low-power encoding techniques. Encoding and decoding methods have been
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24

Long, Sharon C., Catalina Arango P., and Jeanine D. Plummer. "An optimized enumeration method for sorbitol-fermenting Bifidobacteria in water samples." Canadian Journal of Microbiology 51, no. 5 (2005): 413–22. http://dx.doi.org/10.1139/w05-017.

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With increased focus on watershed protection under the Surface Water Treatment Rule, indicators that discriminate among sources of microbial inputs (microbial source tracking) are needed to supplement the quantitative information provided by total and fecal coliform measurements for drinking water monitoring. Bifidobacteria are found in the digestive tract and feces of humans and other animals, and also in sewage. Sorbitol is a food additive used exclusively in food intended for human consumption. Therefore, the presence of sorbitol-fermenting Bifidobacteria in environmental waters can be indi
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25

Ivanovic, Snezana, M. Zutic, O. Radanovic, and S. Lilic. "Slaughterhouse: Slaughter place or source of contamination." Biotehnologija u stocarstvu 23, no. 3-4 (2007): 101–7. http://dx.doi.org/10.2298/bah0704101i.

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There are many possibilities of pig carcasses contamination by pathogenic microorganisms, particularly on the slaughter line. The aim of this paper was to affirm a hygienic level of the slaughter line by the enumeration of aerobic bacteria and enterobacteria. Samples were taken by both non-destructive and destructive methods from 4 place on the carcass of 5 pigs, weekly for 15 weeks. The results of examination has shown the hygiene of slaughter line had satisfied and acceptable level. Destructive method of samples was more susceptible than non-destructive method. The obtained results have inte
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26

OTA, Takahiro, Hiroyoshi MORITA, and Akiko MANADA. "A Universal Two-Dimensional Source Coding by Means of Subblock Enumeration." IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E102.A, no. 2 (2019): 440–49. http://dx.doi.org/10.1587/transfun.e102.a.440.

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27

Valaee, S., and P. Kabal. "An Information Theoretic Approach to Source Enumeration in Array Signal Processing." IEEE Transactions on Signal Processing 52, no. 5 (2004): 1171–78. http://dx.doi.org/10.1109/tsp.2004.826168.

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28

Zhang, Yunxia, Nan Hu, and Zhongfu Ye. "A source enumeration method based on subspace orthogonality and bootstrap technique." Signal Processing 93, no. 4 (2013): 972–76. http://dx.doi.org/10.1016/j.sigpro.2012.11.007.

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29

Strachan, N. J. C., M. MacRae, A. Thomson, O. Rotariu, I. D. Ogden, and K. J. Forbes. "Source attribution, prevalence and enumeration of Campylobacter spp. from retail liver." International Journal of Food Microbiology 153, no. 1-2 (2012): 234–36. http://dx.doi.org/10.1016/j.ijfoodmicro.2011.10.033.

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30

George, Karen L., and Joseph O. Falkinham III. "Selective medium for the isolation and enumeration of Mycobacterium avium-intracellulare and M. scrofulaceum." Canadian Journal of Microbiology 32, no. 1 (1986): 10–14. http://dx.doi.org/10.1139/m86-003.

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A medium for the selective isolation and enumeration of Mycobacterium avium-intracellulare and M. scrofulaceum (MAIS) was developed, based upon the ability of these mycobacteria to utilize Tween 80 as sole carbon source and grow optimally at pH 5.5 on a simple mineral salts medium. Representative MAIS strains had higher efficiencies of plating on the Tween 80 medium compared with Middlebrook 7H10. It was shown that nonmycobacterial organisms in natural waters had lower efficiencies of plating on the Tween 80 medium and smaller colonies, thus allowing direct isolation and enumeration of the slo
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31

Griffin, Richard A. "Potential Uses of Administrative Records for Triple System Modeling for Estimation of Census Coverage Error in 2020." Journal of Official Statistics 30, no. 2 (2014): 177–89. http://dx.doi.org/10.2478/jos-2014-0012.

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Abstract Heterogeneity in capture probabilities is known to produce bias in the dual system estimates that have been used to estimate census coverage in U.S. Censuses since 1980. Triple system estimation using an administrative records list as a third source along with the census and coverage measurement survey has the potential to produce estimates with less bias. This is particularly important for hard-to-reach populations. The article presents potential statistical methods for the estimation of net census undercount using three systems for obtaining population information: (1) a decennial c
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32

Huang, Lei, Cheng Qian, Hing Cheung So, and Jun Fang. "Source enumeration for large array using shrinkage-based detectors with small samples." IEEE Transactions on Aerospace and Electronic Systems 51, no. 1 (2015): 344–57. http://dx.doi.org/10.1109/taes.2014.130579.

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33

Pan, Qing, Chao Mei, Nili Tian, Bingo Wing-Kuen Ling, and Everett X. Wang. "Source Enumeration Based on a Uniform Circular Array in a Determined Case." IEEE Transactions on Vehicular Technology 68, no. 1 (2019): 700–712. http://dx.doi.org/10.1109/tvt.2018.2884522.

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34

Lei Huang, Shunjun Wu, and Xia Li. "Reduced-Rank MDL Method for Source Enumeration in High-Resolution Array Processing." IEEE Transactions on Signal Processing 55, no. 12 (2007): 5658–67. http://dx.doi.org/10.1109/tsp.2007.899344.

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35

Sharif, Suliman. "Cocktail Shaker: An open source drug expansion and enumeration library for peptides." Journal of Open Source Software 5, no. 52 (2020): 1992. http://dx.doi.org/10.21105/joss.01992.

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36

Huang, Lei, Yuhang Xiao, Kefei Liu, Hing Cheung So, and Jian-Kang Zhang. "Bayesian Information Criterion for Source Enumeration in Large-Scale Adaptive Antenna Array." IEEE Transactions on Vehicular Technology 65, no. 5 (2016): 3018–32. http://dx.doi.org/10.1109/tvt.2015.2436060.

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37

Liu, Kefei, Hing Cheung So, João Paulo C. L. da Costa, Florian Römer, and Lei Huang. "Efficient source enumeration for accurate direction-of-arrival estimation in threshold region." Digital Signal Processing 23, no. 5 (2013): 1668–77. http://dx.doi.org/10.1016/j.dsp.2013.06.009.

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38

Albertha, Winida, Nurma Midayanti, Putri I. Firdaus, and Ahmad Kosasih. "Assessment of the quality of administrative data for use in a population census; applying census test results in Indonesia." Statistical Journal of the IAOS 36, no. 4 (2020): 925–32. http://dx.doi.org/10.3233/sji-200744.

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BPS-Statistics Indonesia plans to carry out its seventh population census in 2020. In contrast to the traditional method in previous censuses, it will use administrative data obtained from the Ministry of Home Affairs combined with field enumeration. Individual information recorded in the administrative data will be used as the initial data source for the field enumeration as well as to ensure adequate coverage. These changes could be a step towards a register-based census in the future. Given the important role of register data in the upcoming Indonesian census, it is necessary to assess the
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39

Tangkham, Wannee, and Frederick LeMieux. "Antimicrobial Effects of Sulfadimethoxine on Salmonella, Escherichia coli and Aerobic plate count (APC) in Small-Scale Broiler Operations." Journal of Food Research 8, no. 6 (2019): 147. http://dx.doi.org/10.5539/jfr.v8n6p147.

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Poultry is a source of Salmonella and Escherichia coli. Antibiotics can be used to reduce the enumeration and prevalence of these bacteria. The objective of this study was to determine the effects of sulfadimethoxine antibiotic on the enumeration and prevalence of Salmonella, Escherichia coli and aerobic plate count in broilers. Broilers (n = 600) were allotted to two treatments, each with twelve replications. The treatments were control (drinking water without antibiotic) and with antibiotic at 0.05% (wt/vol) sulfadimethoxine. After a six-week period, the enumeration of Salmonella in the expe
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40

Kruse, Sebastian, Zoi Kaoudi, Bertty Contreras-Rojas, Sanjay Chawla, Felix Naumann, and Jorge-Arnulfo Quiané-Ruiz. "RHEEMix in the data jungle: a cost-based optimizer for cross-platform systems." VLDB Journal 29, no. 6 (2020): 1287–310. http://dx.doi.org/10.1007/s00778-020-00612-x.

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AbstractData analytics are moving beyond the limits of a single platform. In this paper, we present the cost-based optimizer of Rheem, an open-source cross-platform system that copes with these new requirements. The optimizer allocates the subtasks of data analytic tasks to the most suitable platforms. Our main contributions are: (i) a mechanism based on graph transformations to explore alternative execution strategies; (ii) a novel graph-based approach to determine efficient data movement plans among subtasks and platforms; and (iii) an efficient plan enumeration algorithm, based on a novel e
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41

Schwartz, Andrew M., Haley A. Marcotte, and Crystal N. Johnson. "Evaluation of Alternative Colony Hybridization Methods for Pathogenic Vibrios." Foods 12, no. 7 (2023): 1472. http://dx.doi.org/10.3390/foods12071472.

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Vibrios, such as Vibrio parahaemolyticus, are naturally occurring halophilic bacteria that are a major cause of foodborne illness. Because of their autochthonous nature, managing vibrio levels in marine and estuarine environments is impossible. Instead, it is crucial to reliably enumerate their abundance to minimize human exposure. One method of achieving this is the direct plating/colony hybridization (DP/CH) method, which has been used to efficiently quantify pathogenic vibrios in oysters and other seafood products. Although successful, the method relies on proprietary resources. We examined
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42

Lei Huang, Teng Long, and Shunjun Wu. "Source Enumeration for High-Resolution Array Processing Using Improved Gerschgorin Radii Without Eigendecomposition." IEEE Transactions on Signal Processing 56, no. 12 (2008): 5916–25. http://dx.doi.org/10.1109/tsp.2008.929331.

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43

Yazdian, E., S. Gazor, and H. Bastani. "Source enumeration in large arrays using moments of eigenvalues and relatively few samples." IET Signal Processing 6, no. 7 (2012): 689. http://dx.doi.org/10.1049/iet-spr.2011.0260.

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44

Li, Enze, Faizan Saleem, Thomas A. Edge, and Herb E. Schellhorn. "Biological Indicators for Fecal Pollution Detection and Source Tracking: A Review." Processes 9, no. 11 (2021): 2058. http://dx.doi.org/10.3390/pr9112058.

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Fecal pollution, commonly detected in untreated or less treated sewage, is associated with health risks (e.g., waterborne diseases and antibiotic resistance dissemination), ecological issues (e.g., release of harmful gases in fecal sludge composting, proliferative bacterial/algal growth due to high nutrient loads) and economy losses (e.g., reduced aqua farm harvesting). Therefore, the discharge of untreated domestic sewage to the environment and its agricultural reuse are growing concerns. The goals of fecal pollution detection include fecal waste source tracking and identifying the presence o
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45

Deep, Shaleen, Xiao Hu, and Paraschos Koutris. "Ranked enumeration of join queries with projections." Proceedings of the VLDB Endowment 15, no. 5 (2022): 1024–37. http://dx.doi.org/10.14778/3510397.3510401.

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Join query evaluation with ordering is a fundamental data processing task in relational database management systems. SQL and custom graph query languages such as Cypher offer this functionality by allowing users to specify the order via the ORDER BY clause. In many scenarios, the users also want to see the first k results quickly (expressed by the LIMIT clause), but the value of k is not predetermined as user queries are arriving in an online fashion. Recent work has made considerable progress in identifying optimal algorithms for ranked enumeration of join queries that do not contain any proj
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46

Chen, Xiangwei, and Weixing Sheng. "Sequenced Steering Vector Estimation for Eigen-Subspace Projection-Based Robust Adaptive Beamformer." Electronics 12, no. 13 (2023): 2897. http://dx.doi.org/10.3390/electronics12132897.

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Robust adaptive beamforming (RAB) is essential in many applications to ensure signal-receiving quality when model errors exist. Eigen-subspace projection (ESP), one of the most popular RAB methods, can be used when there are arbitrary model errors. However, a major challenge of ESP is projection subspace selection. Traditional ESP (TESP) treats the signal subspace as the projection subspace; thus, source enumeration is required to obtain prior information. Another inherent defect is its poor performance at low signal-to-noise ratios (SNRs). To overcome these drawbacks, two improved ESP-based R
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47

Lakatos, Judit. "Hungarians working abroad, non-residents working in Hungary (Difficulties in the statistical enumeration)." Hungarian Statistical Review 93, Special number 20 (2016): 3–19. http://dx.doi.org/10.20311/stat2016.k20.en003.

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Although the understanding of international migration is important for both the countries of origin and countries of destination, the tools of statistics are quite insufficient. The EU LFS (EU Labour Force Survey), which may be considered as mirror statistics and a target survey as well, is an important data source, nevertheless, methodological pitfalls may occur. Until the recent years, Hungary was hardly affected by the migration process of the EU, so its recording was less important. As a result of the 2008 crisis, however, the number of people working abroad has increased, and the growth w
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48

Liu, Z. M., Z. Y. Lu, Z. T. Huang, and Y. Y. Zhou. "Improved Gerschgorin disk estimator for source enumeration with robustness against spatially non-uniform noise." IET Radar, Sonar & Navigation 5, no. 9 (2011): 952. http://dx.doi.org/10.1049/iet-rsn.2011.0188.

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49

Ayu, Natasya Dia, Nofa Ageng Anggraeni, and Nove Annisa. "Manajemen Pengelolaan Wisata Sumber Jiput." Aktualisasi Pengabdian Masyarakat 1, no. 1 (2023): 30–44. http://dx.doi.org/10.30762/akdimas.v1i1.1538.

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Tourism is an integral part of human life, especially regarding socio-economic activities. Sumber Jiput Tourism is a tour that still exists and is still visited by many people. The role of the local community in the management of the Jiput source tourism object is very important for the continuation of tourism and tourists. The Karang Taruna community is the manager as well as the tourism cultivator. With the times and also the existence of assistance from the Kediri government's youth tourism culture and sports department, the management of the Jiput source tourism continues to improve ideas
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50

Wang, Yishu, Arnaud Mary, Marie-France Sagot, and Blerina Sinaimeri. "Capybara: equivalence ClAss enumeration of coPhylogenY event-BAsed ReconciliAtions." Bioinformatics 36, no. 14 (2020): 4197–99. http://dx.doi.org/10.1093/bioinformatics/btaa498.

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Abstract Motivation Phylogenetic tree reconciliation is the method of choice in analyzing host-symbiont systems. Despite the many reconciliation tools that have been proposed in the literature, two main issues remain unresolved: (i) listing suboptimal solutions (i.e. whose score is ‘close’ to the optimal ones) and (ii) listing only solutions that are biologically different ‘enough’. The first issue arises because the optimal solutions are not always the ones biologically most significant; providing many suboptimal solutions as alternatives for the optimal ones is thus very useful. The second o
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