Fuzzy weight. by Sultan H. Almotiri (14029251)

“…Our study addresses five major components of the quantum method to overcome these challenges: lattice-based cryptography, fully homomorphic algorithms, quantum key distribution, quantum hash functions, and blind quantum algorithms. …”

Block diagram of lattice-based cryptography. by Sultan H. Almotiri (14029251)

“…Our study addresses five major components of the quantum method to overcome these challenges: lattice-based cryptography, fully homomorphic algorithms, quantum key distribution, quantum hash functions, and blind quantum algorithms. …”

Weight of the quantum techniques. by Sultan H. Almotiri (14029251)

“…Our study addresses five major components of the quantum method to overcome these challenges: lattice-based cryptography, fully homomorphic algorithms, quantum key distribution, quantum hash functions, and blind quantum algorithms. …”

Block description of homomorphic encryption. by Sultan H. Almotiri (14029251)

“…Our study addresses five major components of the quantum method to overcome these challenges: lattice-based cryptography, fully homomorphic algorithms, quantum key distribution, quantum hash functions, and blind quantum algorithms. …”

Fuzzy pairwise comparison matrix. by Sultan H. Almotiri (14029251)

“…Our study addresses five major components of the quantum method to overcome these challenges: lattice-based cryptography, fully homomorphic algorithms, quantum key distribution, quantum hash functions, and blind quantum algorithms. …”

Triangular fuzzy numbers. by Sultan H. Almotiri (14029251)

“…Our study addresses five major components of the quantum method to overcome these challenges: lattice-based cryptography, fully homomorphic algorithms, quantum key distribution, quantum hash functions, and blind quantum algorithms. …”

Fuzzy AHP process. by Sultan H. Almotiri (14029251)

“…Our study addresses five major components of the quantum method to overcome these challenges: lattice-based cryptography, fully homomorphic algorithms, quantum key distribution, quantum hash functions, and blind quantum algorithms. …”

Normalized weight. by Sultan H. Almotiri (14029251)

“…Our study addresses five major components of the quantum method to overcome these challenges: lattice-based cryptography, fully homomorphic algorithms, quantum key distribution, quantum hash functions, and blind quantum algorithms. …”

Meta-analysis of some recent related works. by Sultan H. Almotiri (14029251)

“…Our study addresses five major components of the quantum method to overcome these challenges: lattice-based cryptography, fully homomorphic algorithms, quantum key distribution, quantum hash functions, and blind quantum algorithms. …”

Triangular fuzzy number scale. by Sultan H. Almotiri (14029251)

“…Our study addresses five major components of the quantum method to overcome these challenges: lattice-based cryptography, fully homomorphic algorithms, quantum key distribution, quantum hash functions, and blind quantum algorithms. …”

Hierarchy of quantum techniques and alternatives. by Sultan H. Almotiri (14029251)

“…Our study addresses five major components of the quantum method to overcome these challenges: lattice-based cryptography, fully homomorphic algorithms, quantum key distribution, quantum hash functions, and blind quantum algorithms. …”

Crisp weight. by Sultan H. Almotiri (14029251)

“…Our study addresses five major components of the quantum method to overcome these challenges: lattice-based cryptography, fully homomorphic algorithms, quantum key distribution, quantum hash functions, and blind quantum algorithms. …”

Fig 6 - by Sarah A. Alzakari (19704611)

Incremental Inverse Design of Desired Soybean Phenotypes by Joseph Zavorskas (19761296)

“…The limitations of inverse design in genotype-to-bulk phenotype (G-BP) mapping can be addressed via an established design paradigm: “design, build, test, learn” (DBTL), where computational inverse design automates both the design and learn phases. In any context, inverse design is limited by the fundamental “one-to-many” nature of the inverse function. …”

Computational Pipeline for Accelerating the Design of Glycomimetics by Yao Xiao (227567)

Distribution of the average embeddings. by Yiming Kuang (22120458)

Strategic Integration of Machine Learning in the Design of Excellent Hybrid Perovskite Solar Cells by Zhaosheng Zhang (4603021)

“…The ideal combination of descriptors and algorithms identified was MBTR + CustomCNN, with an <i>R</i>² of 0.94. …”

Table 1_SRC is a potential target of Arctigenin in treating triple-negative breast cancer: based on machine learning algorithms, molecular modeling and in Vitro test.xlsx by Yuezhou Huang (9998177)

“…Machine learning algorithms were employed to identify hub genes, followed by validation through molecular docking, molecular dynamics (MD) simulations, and surface plasmon resonance (SPR) assays. …”

Table 2_SRC is a potential target of Arctigenin in treating triple-negative breast cancer: based on machine learning algorithms, molecular modeling and in Vitro test.xlsx by Yuezhou Huang (9998177)

“…Machine learning algorithms were employed to identify hub genes, followed by validation through molecular docking, molecular dynamics (MD) simulations, and surface plasmon resonance (SPR) assays. …”

Table 3_SRC is a potential target of Arctigenin in treating triple-negative breast cancer: based on machine learning algorithms, molecular modeling and in Vitro test.docx by Yuezhou Huang (9998177)

“…Machine learning algorithms were employed to identify hub genes, followed by validation through molecular docking, molecular dynamics (MD) simulations, and surface plasmon resonance (SPR) assays. …”