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Building Combinatorial Test Input Model from Use Case Artefacts.

, , , and . ICST Workshops, page 220-228. IEEE Computer Society, (2017)

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Building Combinatorial Test Input Model from Use Case Artefacts., , , and . ICST Workshops, page 220-228. IEEE Computer Society, (2017)Reducing power in superscalar processor caches using subbanking, multiple line buffers and bit-line segmentation., and . ISLPED, page 70-75. ACM, (1999)A novel apache spark-based 14-dimensional scalable feature extraction approach for the clustering of genomics data., , , , , , and . J. Supercomput., 80 (3): 3554-3588 (February 2024)A Novel Scalable Apache Spark Based Feature Extraction Approaches for Huge Protein Sequence and their Clustering Performance Analysis., , , , , , , and . CoRR, (2022)Scalable incremental fuzzy consensus clustering algorithm for handling big data., , , , , and . Soft Comput., 25 (13): 8703-8719 (2021)Scalable Fuzzy Clustering-based Regression to Predict the Isoelectric Points of the Plant Protein Sequences using Apache Spark., , , , and . FUZZ-IEEE, page 1-6. IEEE, (2021)HPC Based Scalable Logarithmic Kernelized Fuzzy Clustering Algorithms for Handling Big Data., , , , , , and . ICONIP (5), volume 1792 of Communications in Computer and Information Science, page 205-215. Springer, (2022)An incremental clustering method based on multiple objectives for dynamic data analysis., , , , , , and . Multim. Tools Appl., 83 (13): 38145-38165 (April 2024)Probabilistically Sampled and Spectrally Clustered Plant Genotypes using Phenotypic Characteristics., , , and . CoRR, (2020)Vector Quantized Spectral Clustering applied to Soybean Whole Genome Sequences., , , , , and . CoRR, (2018)