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2020 – today
- 2024
[c84]Nathaniel Wesley Filardo
, Brett F. Gutstein, Jonathan Woodruff, Jessica Clarke, Peter Rugg, Brooks Davis, Mark Johnston, Robert M. Norton, David Chisnall, Simon W. Moore, Peter G. Neumann, Robert N. M. Watson:
Cornucopia Reloaded: Load Barriers for CHERI Heap Temporal Safety. ASPLOS (2) 2024: 251-268
2010 – 2019
- 2019
- [j26]Wenlong Fu, Mengjie Zhang, Mark Johnston:
Bayesian genetic programming for edge detection. Soft Comput. 23(12): 4097-4112 (2019) - 2018
- [j25]Wenlong Fu, Bing Xue, Mengjie Zhang, Mark Johnston:
Fast Unsupervised Edge Detection Using Genetic Programming [Application Notes]. IEEE Comput. Intell. Mag. 13(4): 46-58 (2018) - 2017
- [j24]Harith Al-Sahaf, Ausama Al-Sahaf, Bing Xue, Mark Johnston, Mengjie Zhang:
Automatically Evolving Rotation-Invariant Texture Image Descriptors by Genetic Programming. IEEE Trans. Evol. Comput. 21(1): 83-101 (2017) - [j23]Harith Al-Sahaf, Mengjie Zhang, Ausama Al-Sahaf, Mark Johnston:
Keypoints Detection and Feature Extraction: A Dynamic Genetic Programming Approach for Evolving Rotation-Invariant Texture Image Descriptors. IEEE Trans. Evol. Comput. 21(6): 825-844 (2017) - 2016
- [j22]Harith Al-Sahaf, Mengjie Zhang, Mark Johnston:
Binary Image Classification: A Genetic Programming Approach to the Problem of Limited Training Instances. Evol. Comput. 24(1): 143-182 (2016) - [j21]Wenlong Fu, Mark Johnston, Mengjie Zhang:
Genetic programming for edge detection: a Gaussian-based approach. Soft Comput. 20(3): 1231-1248 (2016) - [c83]John Park, Yi Mei, Su Nguyen, Gang Chen, Mark Johnston, Mengjie Zhang:
Genetic Programming Based Hyper-heuristics for Dynamic Job Shop Scheduling: Cooperative Coevolutionary Approaches. EuroGP 2016: 115-132 - 2015
- [j20]Wenlong Fu, Mark Johnston, Mengjie Zhang:
Distribution-based invariant feature construction using genetic programming for edge detection. Soft Comput. 19(8): 2371-2389 (2015) - [j19]Juan Rada-Vilela, Mark Johnston, Mengjie Zhang:
Population statistics for particle swarm optimization: Single-evaluation methods in noisy optimization problems. Soft Comput. 19(9): 2691-2716 (2015) - [j18]Juan Rada-Vilela, Mark Johnston, Mengjie Zhang:
Population statistics for particle swarm optimization: Hybrid methods in noisy optimization problems. Swarm Evol. Comput. 22: 15-29 (2015) - [j17]Su Nguyen, Mengjie Zhang, Mark Johnston, Kay Chen Tan:
Automatic Programming via Iterated Local Search for Dynamic Job Shop Scheduling. IEEE Trans. Cybern. 45(1): 1-14 (2015) - [c82]Wenlong Fu, Mengjie Zhang, Mark Johnston:
Genetic Programming for Extracting Edge Features Using Two Blocks. AusDM 2015: 141-150 - [c81]Harith Al-Sahaf, Mengjie Zhang, Mark Johnston, Brijesh K. Verma:
Image descriptor: A genetic programming approach to multiclass texture classification. CEC 2015: 2460-2467 - [c80]John Park, Su Nguyen, Mengjie Zhang, Mark Johnston:
Evolving Ensembles of Dispatching Rules Using Genetic Programming for Job Shop Scheduling. EuroGP 2015: 92-104 - [c79]Richard J. Marshall, Mark Johnston, Mengjie Zhang:
Hyper-heuristic Operator Selection and Acceptance Criteria. EvoCOP 2015: 99-113 - [c78]Rachel Hunt, Mark Johnston, Mengjie Zhang:
Using Local Search to Evaluate Dispatching Rules in Dynamic Job Shop Scheduling. EvoCOP 2015: 222-233 - [c77]Harith Al-Sahaf, Mengjie Zhang, Mark Johnston:
Evolutionary Image Descriptor: A Dynamic Genetic Programming Representation for Feature Extraction. GECCO 2015: 975-982 - [c76]John Park, Su Nguyen, Mengjie Zhang, Mark Johnston:
A Single Population Genetic Programming based Ensemble Learning Approach to Job Shop Scheduling. GECCO (Companion) 2015: 1451-1452 - 2014
- [j16]Su Nguyen, Mengjie Zhang, Mark Johnston, Kay Chen Tan:
Genetic Programming for Evolving Due-Date Assignment Models in Job Shop Environments. Evol. Comput. 22(1): 105-138 (2014) - [j15]Mark Johnston, Mike Wright:
Prior analysis and scheduling of the 2011 Rugby Union ITM Cup in New Zealand. J. Oper. Res. Soc. 65(8): 1292-1300 (2014) - [j14]Juan Rada-Vilela, Mark Johnston, Mengjie Zhang:
Deception, blindness and disorientation in particle swarm optimization applied to noisy problems. Swarm Intell. 8(4): 247-273 (2014) - [j13]Juan Rada-Vilela, Mark Johnston, Mengjie Zhang:
Population statistics for particle swarm optimization: Resampling methods in noisy optimization problems. Swarm Evol. Comput. 17: 37-59 (2014) - [j12]Wenlong Fu, Mark Johnston, Mengjie Zhang:
Low-Level Feature Extraction for Edge Detection Using Genetic Programming. IEEE Trans. Cybern. 44(8): 1459-1472 (2014) - [j11]Su Nguyen, Mengjie Zhang, Mark Johnston, Kay Chen Tan:
Automatic Design of Scheduling Policies for Dynamic Multi-objective Job Shop Scheduling via Cooperative Coevolution Genetic Programming. IEEE Trans. Evol. Comput. 18(2): 193-208 (2014) - [j10]Urvesh Bhowan, Mark Johnston, Mengjie Zhang, Xin Yao:
Reusing Genetic Programming for Ensemble Selection in Classification of Unbalanced Data. IEEE Trans. Evol. Comput. 18(6): 893-908 (2014) - [c75]Wenlong Fu, Mark Johnston, Mengjie Zhang:
Unsupervised learning for edge detection using Genetic Programming. IEEE Congress on Evolutionary Computation 2014: 117-124 - [c74]Rachel Hunt, Mark Johnston, Mengjie Zhang:
Evolving machine-specific dispatching rules for a two-machine job shop using genetic programming. IEEE Congress on Evolutionary Computation 2014: 618-625 - [c73]Su Nguyen, Mengjie Zhang, Mark Johnston:
A sequential genetic programming method to learn forward construction heuristics for order acceptance and scheduling. IEEE Congress on Evolutionary Computation 2014: 1824-1831 - [c72]Su Nguyen, Mengjie Zhang, Mark Johnston:
Enhancing Branch-and-Bound Algorithms for Order Acceptance and Scheduling with Genetic Programming. EuroGP 2014: 124-136 - [c71]Wenlong Fu, Mark Johnston, Mengjie Zhang:
Is a Single Image Sufficient for Evolving Edge Features by Genetic Programming? EvoApplications 2014: 451-463 - [c70]Richard J. Marshall, Mark Johnston, Mengjie Zhang:
Hyper-heuristics, grammatical evolution and the capacitated vehicle routing problem. GECCO (Companion) 2014: 71-72 - [c69]Rachel Hunt, Mark Johnston, Mengjie Zhang:
Evolving "less-myopic" scheduling rules for dynamic job shop scheduling with genetic programming. GECCO 2014: 927-934 - [c68]Harith Al-Sahaf, Mengjie Zhang, Mark Johnston:
Genetic Programming Evolved Filters from a Small Number of Instances for Multiclass Texture Classification. IVCNZ 2014: 84 - [c67]Harith Al-Sahaf, Mengjie Zhang, Mark Johnston:
Genetic Programming for Multiclass Texture Classification Using a Small Number of Instances. SEAL 2014: 335-346 - [c66]Richard J. Marshall, Mark Johnston, Mengjie Zhang:
A Comparison between Two Evolutionary Hyper-Heuristics for Combinatorial Optimisation. SEAL 2014: 618-630 - [c65]Su Nguyen, Mengjie Zhang, Mark Johnston, Kay Chen Tan:
Selection Schemes in Surrogate-Assisted Genetic Programming for Job Shop Scheduling. SEAL 2014: 656-667 - [c64]Richard J. Marshall, Mark Johnston, Mengjie Zhang:
Developing a Hyper-Heuristic Using Grammatical Evolution and the Capacitated Vehicle Routing Problem. SEAL 2014: 668-679 - [c63]John Park, Su Nguyen, Mengjie Zhang, Mark Johnston:
Enhancing Heuristics for Order Acceptance and Scheduling Using Genetic Programming. SEAL 2014: 723-734 - [c62]Wenlong Fu, Mark Johnston, Mengjie Zhang:
Automatic Resolution Selection for Edge Detection Using Genetic Programming. SEAL 2014: 810-821 - 2013
- [j9]Su Nguyen, Mengjie Zhang, Mark Johnston, Kay Chen Tan:
Hybrid evolutionary computation methods for quay crane scheduling problems. Comput. Oper. Res. 40(8): 2083-2093 (2013) - [j8]Mahdi Setayesh, Mengjie Zhang, Mark Johnston:
A novel particle swarm optimisation approach to detecting continuous, thin and smooth edges in noisy images. Inf. Sci. 246: 28-51 (2013) - [j7]Urvesh Bhowan, Mark Johnston, Mengjie Zhang, Xin Yao:
Evolving Diverse Ensembles Using Genetic Programming for Classification With Unbalanced Data. IEEE Trans. Evol. Comput. 17(3): 368-386 (2013) - [j6]Su Nguyen, Mengjie Zhang, Mark Johnston, Kay Chen Tan:
A Computational Study of Representations in Genetic Programming to Evolve Dispatching Rules for the Job Shop Scheduling Problem. IEEE Trans. Evol. Comput. 17(5): 621-639 (2013) - [c61]Harith Al-Sahaf, Mengjie Zhang, Mark Johnston:
A One-Shot Learning Approach to Image Classification Using Genetic Programming. Australasian Conference on Artificial Intelligence 2013: 110-122 - [c60]John Park, Su Nguyen, Mark Johnston, Mengjie Zhang:
Evolving Stochastic Dispatching Rules for Order Acceptance and Scheduling via Genetic Programming. Australasian Conference on Artificial Intelligence 2013: 478-489 - [c59]Juan Rada-Vilela, Mengjie Zhang, Mark Johnston:
Resampling in Particle Swarm Optimization. IEEE Congress on Evolutionary Computation 2013: 947-954 - [c58]John Park, Su Nguyen, Mengjie Zhang, Mark Johnston:
Genetic programming for order acceptance and scheduling. IEEE Congress on Evolutionary Computation 2013: 1005-1012 - [c57]Wenlong Fu, Mark Johnston, Mengjie Zhang:
Triangular-distribution-based feature construction using Genetic Programming for edge detection. IEEE Congress on Evolutionary Computation 2013: 1732-1739 - [c56]Su Nguyen, Mengjie Zhang, Mark Johnston, Kay Chen Tan:
Learning Reusable Initial Solutions for Multi-objective Order Acceptance and Scheduling Problems with Genetic Programming. EuroGP 2013: 157-168 - [c55]Wenlong Fu, Mark Johnston, Mengjie Zhang:
Genetic Programming for Automatic Construction of Variant Features in Edge Detection. EvoApplications 2013: 354-364 - [c54]Wenlong Fu, Mark Johnston, Mengjie Zhang:
Automatic Construction of Gaussian-Based Edge Detectors Using Genetic Programming. EvoApplications 2013: 365-375 - [c53]Juan Rada-Vilela, Mengjie Zhang, Mark Johnston:
Optimal computing budget allocation in particle swarm optimization. GECCO 2013: 81-88 - [c52]Urvesh Bhowan, Mark Johnston, Mengjie Zhang:
Comparing ensemble learning approaches in genetic programming for classification with unbalanced data. GECCO (Companion) 2013: 135-136 - [c51]Wenlong Fu, Mark Johnston, Mengjie Zhang:
Genetic programming for edge detection using multivariate density. GECCO 2013: 917-924 - [c50]Harith Al-Sahaf, Mengjie Zhang, Mark Johnston:
Binary image classification using genetic programming based on local binary patterns. IVCNZ 2013: 220-225 - [c49]Wenlong Fu, Mark Johnston, Mengjie Zhang:
Investigation of low-level edge feature extraction using three blocks. IVCNZ 2013: 293-298 - [c48]Wenlong Fu, Mark Johnston, Mengjie Zhang:
Gaussian mixture models and information entropy for image segmentation using particle swarm optimisation. IVCNZ 2013: 328-333 - [p1]Su Nguyen, Mengjie Zhang, Mark Johnston, Kay Chen Tan:
Dynamic Multi-objective Job Shop Scheduling: A Genetic Programming Approach. Automated Scheduling and Planning 2013: 251-282 - 2012
- [j5]Jeffrey Chang, Mark Johnston:
Cloud Computing in Local Government: From the Perspective of Four London Borough Councils. Int. J. Cloud Appl. Comput. 2(4): 1-15 (2012) - [j4]Urvesh Bhowan, Mark Johnston, Mengjie Zhang:
Developing New Fitness Functions in Genetic Programming for Classification With Unbalanced Data. IEEE Trans. Syst. Man Cybern. Part B 42(2): 406-421 (2012) - [c47]Wenlong Fu, Mark Johnston, Mengjie Zhang:
Automatic Construction of Invariant Features Using Genetic Programming for Edge Detection. Australasian Conference on Artificial Intelligence 2012: 144-155 - [c46]Aaron Scoble, Mark Johnston, Mengjie Zhang:
Local Search in Parallel Linear Genetic Programming for Multiclass Classification. Australasian Conference on Artificial Intelligence 2012: 373-384 - [c45]Wenlong Fu, Mark Johnston, Mengjie Zhang:
Genetic programming for edge detection via balancing individual training images. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c44]Wenlong Fu, Mark Johnston, Mengjie Zhang:
Soft edge maps from edge detectors evolved by genetic programming. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c43]Su Nguyen, Mengjie Zhang, Mark Johnston, Kay Chen Tan:
A coevolution genetic programming method to evolve scheduling policies for dynamic multi-objective job shop scheduling problems. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c42]Mahdi Setayesh, Mengjie Zhang, Mark Johnston:
Effects of static and dynamic topologies in Particle Swarm Optimisation for edge detection in noisy images. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c41]Su Nguyen, Mengjie Zhang, Mark Johnston, Kay Chen Tan:
Evolving Reusable Operation-Based Due-Date Assignment Models for Job Shop Scheduling with Genetic Programming. EuroGP 2012: 121-133 - [c40]Wenlong Fu, Mark Johnston, Mengjie Zhang:
Genetic programming for edge detection using blocks to extract features. GECCO 2012: 855-862 - [c39]Mahdi Setayesh, Mengjie Zhang, Mark Johnston:
A spatial random-meaningful neighbourhood topology in pso for edge detection in noisy images. GECCO (Companion) 2012: 1403-1404 - [c38]Wenlong Fu, Mark Johnston, Mengjie Zhang:
Genetic programming for edge detection based on figure of merit. GECCO (Companion) 2012: 1483-1484 - [c37]Wenlong Fu, Mark Johnston, Mengjie Zhang:
Multi-frequency transformation for edge detection. IVCNZ 2012: 204-209 - [c36]Wenlong Fu, Mark Johnston, Mengjie Zhang:
Figure of Merit Based Fitness Functions in Genetic Programming for Edge Detection. SEAL 2012: 22-31 - [c35]Su Nguyen, Mengjie Zhang, Mark Johnston, Kay Chen Tan:
Automatic Discovery of Optimisation Search Heuristics for Two Dimensional Strip Packing Using Genetic Programming. SEAL 2012: 341-350 - 2011
- [j3]Ammar W. Mohemmed, Mark Johnston, Mengjie Zhang:
Particle swarm optimisation based AdaBoost for object detection. Soft Comput. 15(9): 1793-1805 (2011) - [c34]Urvesh Bhowan, Mark Johnston, Mengjie Zhang:
Ensemble Learning and Pruning in Multi-Objective Genetic Programming for Classification with Unbalanced Data. Australasian Conference on Artificial Intelligence 2011: 192-202 - [c33]Wenlong Fu, Mark Johnston, Mengjie Zhang:
Genetic Programming for Edge Detection Based on Accuracy of Each Training Image. Australasian Conference on Artificial Intelligence 2011: 301-310 - [c32]Rachel Hunt, Mark Johnston, Mengjie Zhang:
Improving Robustness of Multiple-Objective Genetic Programming for Object Detection. Australasian Conference on Artificial Intelligence 2011: 311-320 - [c31]Aaron Scoble, Mark Johnston, Mengjie Zhang:
Eliminating Useless Object Detectors Evolved in Multiple-Objective Genetic Programming. Australasian Conference on Artificial Intelligence 2011: 341-350 - [c30]Mahdi Setayesh, Mengjie Zhang, Mark Johnston:
Investigating Particle Swarm Optimisation Topologies for Edge Detection in Noisy Images. Australasian Conference on Artificial Intelligence 2011: 609-618 - [c29]Mahdi Setayesh, Mengjie Zhang, Mark Johnston:
Edge detection using constrained discrete particle swarm optimisation in noisy images. IEEE Congress on Evolutionary Computation 2011: 246-253 - [c28]Wenlong Fu, Mark Johnston, Mengjie Zhang:
Genetic programming for edge detection: A global approach. IEEE Congress on Evolutionary Computation 2011: 254-261 - [c27]Wenlong Fu, Mark Johnston, Mengjie Zhang:
A Hybrid Particle Swarm Optimisation with Differential Evolution Approach to Image Segmentation. EvoApplications (1) 2011: 173-182 - [c26]Mahdi Setayesh, Mengjie Zhang, Mark Johnston:
Detection of continuous, smooth and thin edges in noisy images using constrained particle swarm optimisation. GECCO 2011: 45-52 - [c25]Wenlong Fu, Mark Johnston, Mengjie Zhang:
Hybrid particle swarm optimisation based on history information sharing. GECCO 2011: 77-84 - [c24]Su Nguyen, Mengjie Zhang, Mark Johnston:
A genetic programming based hyper-heuristic approach for combinatorial optimisation. GECCO 2011: 1299-1306 - [c23]Urvesh Bhowan, Mark Johnston, Mengjie Zhang:
Evolving ensembles in multi-objective genetic programming for classification with unbalanced data. GECCO 2011: 1331-1338 - [c22]Sooraj KuttyKrishnan, Jeffrey Sabina, Laura Langton, Mark Johnston, Michael R. Brent:
A Quantitative Model of Glucose Signaling in Yeast Reveals an Incoherent Feed Forward Loop Leading to a Specific, Transient Pulse of Transcription. RECOMB 2011: 153 - 2010
- [c21]Urvesh Bhowan, Mengjie Zhang, Mark Johnston:
A Comparison of Classification Strategies in Genetic Programming with Unbalanced Data. Australasian Conference on Artificial Intelligence 2010: 243-252 - [c20]Rachel Hunt, Mark Johnston, Will N. Browne, Mengjie Zhang:
Sampling Methods in Genetic Programming for Classification with Unbalanced Data. Australasian Conference on Artificial Intelligence 2010: 273-282 - [c19]Wenlong Fu, Mark Johnston, Mengjie Zhang:
Hybrid Particle Swarm Optimisation Algorithms Based on Differential Evolution and Local Search. Australasian Conference on Artificial Intelligence 2010: 313-322 - [c18]Mahdi Setayesh, Mark Johnston, Mengjie Zhang:
Edge and Corner Extraction Using Particle Swarm Optimisation. Australasian Conference on Artificial Intelligence 2010: 323-333 - [c17]David Kinzett, Mengjie Zhang, Mark Johnston:
Investigation of simplification threshold and noise level of input data in numerical simplification of genetic programs. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c16]Thomas Liddle, Mark Johnston, Mengjie Zhang:
Multi-Objective Genetic Programming for object detection. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c15]Urvesh Bhowan, Mengjie Zhang, Mark Johnston:
Genetic Programming for Classification with Unbalanced Data. EuroGP 2010: 1-13 - [c14]Mark Johnston, Thomas Liddle, Mengjie Zhang:
A Relaxed Approach to Simplification in Genetic Programming. EuroGP 2010: 110-121 - [c13]David Kinzett, Mengjie Zhang, Mark Johnston:
Analysis of Building Blocks with Numerical Simplification in Genetic Programming. EuroGP 2010: 289-300 - [c12]Urvesh Bhowan, Mengjie Zhang, Mark Johnston:
AUC analysis of the pareto-front using multi-objective GP for classification with unbalanced data. GECCO 2010: 845-852
2000 – 2009
- 2009
- [j2]David Kinzett, Mark Johnston, Mengjie Zhang:
Numerical simplification for bloat control and analysis of building blocks in genetic programming. Evol. Intell. 2(4): 151-168 (2009) - [c11]Urvesh Bhowan, Mengjie Zhang, Mark Johnston:
Multi-Objective Genetic Programming for Classification with Unbalanced Data. Australasian Conference on Artificial Intelligence 2009: 370-380 - [c10]Ammar W. Mohemmed, Mengjie Zhang, Mark Johnston:
Particle Swarm Optimization based Adaboost for face detection. IEEE Congress on Evolutionary Computation 2009: 2494-2501 - [c9]Urvesh Bhowan, Mark Johnston, Mengjie Zhang:
Differentiating between individual class performance in Genetic Programming fitness for classification with unbalanced data. IEEE Congress on Evolutionary Computation 2009: 2802-2809 - [c8]Ammar W. Mohemmed, Mark Johnston, Mengjie Zhang:
Particle swarm optimization based multi-prototype ensembles. GECCO 2009: 57-64 - [c7]David Kinzett, Mark Johnston, Mengjie Zhang:
How online simplification affects building blocks in genetic programming. GECCO 2009: 979-986 - 2008
- [c6]Huayang Xie, Mengjie Zhang, Peter Andreae, Mark Johnston:
Is the not-sampled issue in tournament selection critical? IEEE Congress on Evolutionary Computation 2008: 3710-3717 - [c5]Huayang Xie, Mengjie Zhang, Peter Andreae, Mark Johnston:
An analysis of multi-sampled issue and no-replacement tournament selection. GECCO 2008: 1323-1330 - [c4]Ammar W. Mohemmed, Mengjie Zhang, Mark Johnston:
A PSO Based Adaboost Approach to Object Detection. SEAL 2008: 81-90 - [c3]David Kinzett, Mengjie Zhang, Mark Johnston:
Using Numerical Simplification to Control Bloat in Genetic Programming. SEAL 2008: 493-502 - 2007
- [c2]Kourosh Neshatian, Mengjie Zhang, Mark Johnston:
Feature Construction and Dimension Reduction Using Genetic Programming. Australian Conference on Artificial Intelligence 2007: 160-170
1990 – 1999
- 1999
- [c1]Mark Johnston:
Application of Domain Testing to Reliability Amplification. Applied Informatics 1999: 392-394
1980 – 1989
- 1983
- [j1]Leonard Goddard, Mark Johnston:
The nature of reflexive paradoxes. I. Notre Dame J. Formal Log. 24(4): 491-508 (1983)
Coauthor Index
[j26] [j25] [j24] [j23] [j22] [j21] [c83] [j20] [j19] [j18] [j17] [c82] [c81] [c80] [c79] [c78] [c77] [c76] [j16] [j14] [j13] [j12] [j11] [j10] [c75] [c74] [c73] [c72] [c71] [c70] [c69] [c68] [c67] [c66] [c65] [c64] [c63] [c62] [j9] [j8] [j7] [j6] [c61] [c60] [c59] [c58] [c57] [c56] [c55] [c54] [c53] [c52] [c51] [c50] [c49] [c48] [p1] [j4] [c47] [c46] [c45] [c44] [c43] [c42] [c41] [c40] [c39] [c38] [c37] [c36] [c35] [j3] [c34] [c33] [c32] [c31] [c30] [c29] [c28] [c27] [c26] [c25] [c24] [c23] [c21] [c20] [c19] [c18] [c17] [c16] [c15] [c14] [c13] [c12] [j2] [c11] [c10] [c9] [c8] [c7] [c6] [c5] [c4] [c3] [c2]
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