Results 121 to 130 of about 33,606 (255)

Autonomous Leadership: How Board Independence Shapes Machine Learning Based Corporate Culture in Thailand

Corporate Social Responsibility and Environmental Management, EarlyView.
ABSTRACT Corporate culture is a critical driver of corporate social responsibility, shaping how firms internalize sustainability, social and environmental concerns, yet its governance antecedents are less understood. Motivated by the need to understand how governance structures affect organizational values and behavior, we explore the relationship ...
Sirimon Treepongkaruna, Stefano Starita
wiley   +1 more source

Enhancing Machine Learning Security: The Significance of Realistic Adversarial Examples [PDF]

Adversarial attacks pose a significant security threat in Machine Learning (ML), employing subtle, invisible perturbations on original examples to craft instances that deceive model decisions.
DYRMISHI, Salijona
core  

Research progress and current status of dynamic wave propagation characteristics in rock mass: A review

Deep Underground Science and Engineering, EarlyView.
This review elucidates the velocity–dispersion–attenuation coupling mechanisms of wave propagation in rock masses, compares six representative models, and reveals how pressure, temperature, mineral composition, and anisotropy jointly control dynamic responses in complex geological media.
Jiajun Shu, Tao Li, Ruiqi Yuan, Yue Li, Bingni Wu, Bo Liu, Zhengding Deng, Galindo Rubén, Fausto Molina‐Gómez   +8 more
wiley   +1 more source

Cost-aware adversarial attacks and defences for tabular data

, 2023
LAUREA MAGISTRALEGli adversarial examples (esempi avversari) sono input intenzionalmente creati per ingannare i sistemi di machine learning (apprendimento automatico), inducendoli a produrre output errati.
Cermaria, Francesco
core  

Advances in vital‐sign prediction and early‐warning models for underground coal mine workers integrating environmental factors

Deep Underground Science and Engineering, EarlyView.
This review synthesizes advances in predicting miners' vital signs by integrating environmental monitoring (dust, temperature, and gas) with physiological data. It highlights multi‐source data fusion techniques and early‐warning models for enhanced occupational safety in underground coal mines.
Junji Zhu, Dawei Cui, Yingjie Liu, Yuntao Liang, Yue Zhang   +4 more
wiley   +1 more source

Evasive attacks against autoencoder-based cyberattack detection systems in power systems

Energy and AI
The digital transformation process of power systems towards smart grids is resulting in improved reliability, efficiency and situational awareness at the expense of increased cybersecurity vulnerabilities. Given the availability of large volumes of smart
Yew Meng Khaw, Amir Abiri Jahromi, Mohammadreza F.M. Arani, Deepa Kundur   +3 more
doaj   +1 more source

IML Machine Learning Workshop

, 2017
https://arxiv.org/abs/1701.05927 We provide a bridge between generative modeling in the Machine Learning community and simulated physical processes in High Energy Particle Physics by applying a novel Generative Adversarial Network (GAN) architecture to ...
Paganini, Michela
core  

Computationally Driven Advances in Cu‐CNT On‐Chip Interconnect Materials: From First Principles to Machine Learning

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
A multiscale framework integrating electronic, mechanical, and thermal analysis with machine learning to optimize carbon nanotube interconnects. As the component dimensions in integrated circuits shrink to extreme scales, the complexity of interconnect systems is increasing significantly, necessitating an urgent and comprehensive upgrade of ...
Changhong Zhang, Jie Liang, Yi Li, Zhenyu Wang, Haoyuan Li, Zhen Yuan, Jiuren Zhou, Rongmei Chen, Wensheng Zhao, Lei Zhang, Hanshen Xin, Jianhua Zhang   +11 more
wiley   +1 more source

Adversarial Controls for Scientific Machine Learning

, 2018
New machine learning methods to analyze raw chemical and biological data are now widely accessible as open-source toolkits. This positions researchers to leverage powerful, predictive models in their own domains. We caution, however, that the application
Michael J. Keiser, Kangway V. Chuang, Chuang, Kangway V, Keiser, Michael J   +3 more
core   +1 more source

Collective Grievance Promotes Collective Action and Aggressive Intergroup Inclinations Through Dehumanization Among Conservative Members of Dominant Groups

European Journal of Social Psychology, EarlyView.
ABSTRACT Previous research has focused on disadvantaged groups seeking social change, overlooking how dominant groups mobilize to preserve the status quo. Across three studies (two correlational, one experimental), we explored how collective grievance—the feeling of being or having been collectively wronged by an outgroup—drives system‐preserving ...
Beatriz Alba, Alexandra Vázquez
wiley   +1 more source