Unlocking hidden market segments: A data-driven approach exemplified by the electric vehicle market
Market segmentation is crucial for companies to recognise the distribution of products in the
market and to identify'unexploited'segments that hold the potential for new products not yet …
market and to identify'unexploited'segments that hold the potential for new products not yet …
Optimizing compressive strength prediction using adversarial learning and hybrid regularization
T Aziz, H Aziz, S Mahapakulchai… - Scientific Reports, 2024 - nature.com
The infrastructure industry consumes natural resources and produces construction waste,
which has a detrimental impact on the environment. To mitigate these adverse effects and …
which has a detrimental impact on the environment. To mitigate these adverse effects and …
A Multiscale study of flexible customer's energy demand under smart grid architecture: A modeling and simulation study
In the context of an energy crisis, efficient energy management has become an unavoidable
issue for sustainability, regardless of the domain under consideration. Smart grids are no …
issue for sustainability, regardless of the domain under consideration. Smart grids are no …
Delamination and thrust force analysis in GLARE: Influence of tool geometry and prediction with machine learning models
The multi-layered (fiber/metal) structure of glass fibre aluminium reinforced epoxy (GLARE)
makes it difficult to obtain acceptable damage-free holes that meet aerospace standards …
makes it difficult to obtain acceptable damage-free holes that meet aerospace standards …
Basketball self-evaluation matrix: discrepancy between self-confidence and decision-making performance on psychological profiling of players
Background In basketball training, self-evaluation plays a crucial role in the decision-making
and execution of movements of players. The self-evaluation of players is influenced by their …
and execution of movements of players. The self-evaluation of players is influenced by their …
[HTML][HTML] Novel Cost-Effective and Portable Three-Dimensional Force Measurement System for Biomechanical Analysis: A Reliability and Validity Study
L Hao, C Yin, X Duan, Z Wang, M Zhang - Sensors, 2024 - mdpi.com
The application of dynamic data in biomechanics is crucial; traditional laboratory-level force
measurement systems are precise, but they are costly and limited to fixed environments. To …
measurement systems are precise, but they are costly and limited to fixed environments. To …
Dimensionless Parameters for Waveform Characterization of Acoustic Emission Signals: Application to Sedimentation and Soil Compression Experiments
E Castro, G García-Ros, DX Villalva-León… - Symmetry, 2023 - mdpi.com
Acoustic Emission (AE) is a non-destructive evaluation method that uses transient elastic
waves produced by the sudden release of mechanical energy in a material or structure. This …
waves produced by the sudden release of mechanical energy in a material or structure. This …
Geometry-Inference Based Clustering Heuristic: New k-means Metric for Gaussian Data and Experimental Proof of Concept
K-means is one of the algorithms that are most utilized in data clustering; the number of
metrics is coupled to k-means to reach reasonable levels of clusters' compactness and …
metrics is coupled to k-means to reach reasonable levels of clusters' compactness and …
Ecosystem Services Trade-Offs in the Chaohu Lake Basin Based on Land-Use Scenario Simulations
A Jin, G Zhang, P Ma, X Wang - Land, 2024 - search.proquest.com
Amid global environmental degradation, understanding the spatiotemporal dynamics and
trade-offs of ecosystem services (ESs) under varying land-use scenarios is critical for …
trade-offs of ecosystem services (ESs) under varying land-use scenarios is critical for …
Discriminative Dimension Selection for Enhancing the Interpretability and Performance of Clustering Output
HK Lian, K Waiyamai, S Konstantinos… - … on Knowledge and …, 2024 - ieeexplore.ieee.org
Discriminative Dimension Selection (DDS) has emerged as a powerful tool for identifying the
most relevant features in high-dimensional datasets, enabling interpretable data analysis …
most relevant features in high-dimensional datasets, enabling interpretable data analysis …