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network analysis

Weighted Social Network Analysis

Weighted Social Network Analysis extends classical SNA by assigning numeric values — weights — to ties between actors, capturing tie strength, interaction frequency, or resource flow. Rather than treating all connections as equal, it reveals who holds privileged positions by virtue of the intensity, not merely the exis

2 sources2004
network analysis

Weighted Stochastic Block Model

The Weighted Stochastic Block Model (W-SBM) extends the classical stochastic block model to networks whose edges carry numerical weights. By positing that edge weights between node pairs arise from distributions that depend on the block memberships of those nodes, it simultaneously infers a partition of nodes into comm

2 sources2014
network analysis

Weighted Temporal Network Analysis

Weighted temporal network analysis studies networks whose edges carry numerical weights — representing interaction strength, frequency, or intensity — and whose structure changes over time. It combines the time-varying perspective of temporal network analysis with the quantitative precision of weighted graph metrics, r

2 sources2004
network analysis

Weighted Two-Mode Network Analysis

Weighted two-mode network analysis examines bipartite graphs in which two distinct node sets — such as actors and events, authors and papers, or species and habitats — are connected by edges carrying numerical weights that capture the strength, frequency, or intensity of each affiliation. Incorporating weights provides

2 sources1997
geoscience

Well Log Analysis

Well log analysis is the systematic examination of measurements recorded by instruments lowered into a borehole to characterize subsurface lithology, fluid content, and petrophysical properties. Originating in the 1940s, this method has become indispensable for petroleum exploration, groundwater assessment, and enginee

3 sources1940
signal processing

Wiener Filter

The Wiener filter is an optimal linear filter that minimizes mean-square error between the desired signal and the filter output given knowledge of signal and noise statistics. Developed by Norbert Wiener in 1949, it provides the theoretical foundation for optimal filtering and remains the benchmark against which all ot

2 sources1949
biomechanics

Windkessel Model

The Windkessel model is a lumped-parameter representation of the arterial system that captures the pulsatile dynamics of blood flow and pressure using simple mechanical analogs (resistors and capacitors). Named after the German word for air chamber, it was formalized by Westerhof and colleagues in the late 1960s and re

2 sources1969
text mining

Word Sense Disambiguation

Word sense disambiguation (WSD) is the natural-language-processing task of choosing the correct meaning of a polysemous word from its context. Surveyed by Navigli (2009), it resolves which sense of a many-meaning word applies in a given sentence, improving the quality of information retrieval, machine translation, and

2 sources2009
text mining

Word2Vec

Word2Vec is a neural word-embedding technique introduced by Mikolov and colleagues in 2013 that maps each word in a text corpus to a dense numeric vector. Words that appear in similar contexts end up close together in the vector space, so the embeddings capture semantic similarity that can be measured arithmetically.

1 source2013
meteorology

WRF Model

The Weather Research and Forecasting (WRF) model is a mesoscale atmospheric simulation system used for weather forecasting, research, and climate applications. Developed cooperatively by NCAR, NOAA, and academic institutions, WRF became operational in 2004 and has become one of the most widely used atmospheric models w

2 sources2000
materials science

X-ray Photoelectron Spectroscopy

X-ray Photoelectron Spectroscopy (XPS), also known as Electron Spectroscopy for Chemical Analysis (ESCA), is a surface-sensitive analytical technique that measures the kinetic energies of photoelectrons ejected from a material by high-energy X-rays. Developed by Kai Siegbahn in 1967, XPS determines elemental compositio

3 sources1967
political sociology

Xenophobia Scale

The Xenophobia Scale measures fear, discomfort, or prejudice toward foreign nationals and immigrants. Unlike immigration policy preferences (which can reflect economic or pragmatic considerations), xenophobia captures affective and attitudinal dimensions—emotional threat perception, negative stereotypes, and cultural d

3 sources2009
machine learning

XGBoost

XGBoost (Extreme Gradient Boosting) is a scalable tree-boosting algorithm introduced by Tianqi Chen and Carlos Guestrin in 2016. It builds a strong predictor by adding decision trees one at a time, each correcting the errors left by the trees before it, and is a powerful prediction method widely used in competitions.

1 source2016
materials science

XRD Rietveld Refinement

XRD Rietveld Refinement is a method for extracting detailed crystal structure information from powder diffraction data by comparing observed and calculated diffraction patterns through least-squares refinement. Developed by Hugo Rietveld in 1969, this technique enables determination of atomic positions, occupancies, th

3 sources1969
deep learning

YOLO

YOLO (You Only Look Once) is a single-shot, end-to-end convolutional object detector introduced by Redmon, Divvala, Girshick, and Farhadi at CVPR 2016. It reframes object detection as a single regression problem — predicting bounding box coordinates and class probabilities directly from an image in one forward pass — a

2 sources2016
model evaluation

Youdens J Statistic

Youdens J statistic, also called the Youden index, measures the maximum difference between the true positive rate and false positive rate across different classification thresholds. It is useful for selecting optimal cutoff points in diagnostic testing.

2 sources1950
cryptography

Zero-Knowledge Proof

A zero-knowledge proof is a cryptographic protocol in which a prover can convince a verifier that a statement is true without revealing any additional information beyond the truth of the statement. Introduced by Goldwasser, Micali, and Rackoff in 1985, zero-knowledge proofs have profound applications in authentication,

3 sources1985
text mining

Zero-Shot Classification

Zero-shot classification is a natural-language-processing task that assigns text to categories described in plain language without requiring any labelled training data. Formalised as an entailment problem by Yin, Hay and Roth (2019), it lets a large pretrained language model recognise new categories on the fly simply b

2 sources2019
telecommunications

ZF/MMSE Equalization

Zero-Forcing (ZF) and Minimum Mean-Square Error (MMSE) equalization are fundamental linear receiver algorithms for combating intersymbol interference in dispersive channels. Developed in the context of data transmission theory, these methods form the basis of modern channel equalization in wireless and wired systems. W

2 sources1974
control theory

Ziegler-Nichols Tuning

Ziegler-Nichols Tuning is a practical, model-free method for tuning PID controller gains empirically. Published in 1942, this pioneering method requires only measurement of the system's step response (or closed-loop oscillations), making it applicable to any system without prior identification. Ziegler-Nichols remains

2 sources1942
cryptography

zk-SNARK

A zk-SNARK (Zero-Knowledge Succinct Non-Interactive Argument of Knowledge) is a cryptographic proof system that allows a prover to convince a verifier that a statement is true without revealing any information beyond the statement's validity. The acronym describes its key properties: it requires no interaction, proofs

2 sources2014
cryptography

zk-STARK

A zk-STARK (Zero-Knowledge Scalable Transparent Argument of Knowledge) is a cryptographic proof system allowing a prover to convince a verifier of a computation's correctness without trusted setup or revealing computational details. Introduced by Ben-Sasson and colleagues in 2018, zk-STARKs address a key limitation of

2 sources2018
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