Results 91 to 100 of about 114,527 (276)
The Reality of Non-Adversarial Justice: Principles and Practice
The growth, development and institutionalisation of alternative dispute resolution (ADR) processes in Australia have paved the way for a changing legal culture. Whilst the adversarial process underpins the Australian legal system, the theory and practice of ADR has allowed a broadening of attitudes towards conflict resolution.
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This work presents a novel generative artificial intelligence (AI) framework for inverse alloy design through operations (optimization and diffusion) within learned compact latent space from variational autoencoder (VAE). The proposed work addresses challenges of limited data, nonuniqueness solutions, and high‐dimensional spaces.
Mohammad Abu‐Mualla +4 more
wiley +1 more source
THE ADVERSITY PRINCIPLE IN CRIMINAL PROCEDURE
In criminal procedure, the cornerstone of the proceeding governing the establishment of crucial facts is the opportunity of the parties to present their arguments on the criminal matter at issue and to challenge the opponent’s arguments, which is the ...
Saša Knežević
doaj
Artificial Intelligence for Bone: Theory, Methods, and Applications
Advances in artificial intelligence (AI) offer the potential to improve bone research. The current review explores the contributions of AI to pathological study, biomarker discovery, drug design, and clinical diagnosis and prognosis of bone diseases. We envision that AI‐driven methodologies will enable identifying novel targets for drugs discovery. The
Dongfeng Yuan +3 more
wiley +1 more source
The so-called principle of real truth is argument to justify arbitrary procedures used in criminal proceedings. A perfect reproduction of the scene of a crime is impossible.
Ricardo Alves Domingues +1 more
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DART: A Principled Approach to Adversarially Robust Unsupervised Domain Adaptation
Distribution shifts and adversarial examples are two major challenges for deploying machine learning models. While these challenges have been studied individually, their combination is an important topic that remains relatively under-explored. In this work, we study the problem of adversarial robustness under a common setting of distribution shift ...
Wang, Yunjuan +5 more
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Deep Learning‐Assisted Coherent Raman Scattering Microscopy
The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu +4 more
wiley +1 more source
Automated federated learning‐based adversarial attack and defence in industrial control systems
With the development of deep learning and federated learning (FL), federated intrusion detection systems (IDSs) based on deep learning have played a significant role in securing industrial control systems (ICSs).
Guo‐Qiang Zeng +4 more
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Deep Learning‐Assisted Design of Mechanical Metamaterials
This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong +5 more
wiley +1 more source
Problem of Adversarial Principle in Antimonopoly Trial
The article considers antimonopoly trial in the Russian Federation as a quasi-judicial process, because adversarial nature of the judicial process is to some extent implemented in the Russian antimonopoly ...
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