Results 81 to 90 of about 4,795 (257)

Beyond Initial Adoption: How Lean Six Sigma Is Sustained, Adapted, and Used in the U.S. Textile and Apparel Industry

Quality and Reliability Engineering International, EarlyView.
ABSTRACT This study examines how Lean Six Sigma (LSS) currently functions in the U.S. textile and apparel industry after years of adoption and use. Moving beyond isolated project‐level evidence, this study investigates whether LSS has been implemented as an organizational capability and integrated into the corporate culture, adapted to textile‐specific
Alireza Vahedi Fakhr, A. Blanton Godfrey, Warren J. Jasper   +2 more
wiley   +1 more source

Integrating Image Segmentation and Deep Learning to Improve Radio Frequency Propagation Models

International Journal of Satellite Communications and Networking, EarlyView.
ABSTRACT This paper proposes a multi‐sensor approach to improve radio frequency (RF) propagation models, which play a key role in the rapidly expanding field of connected vehicle technology. Focusing on the 1‐ to 20‐GHz frequency range, which is critical for both satellite‐to‐vehicle and base station‐to‐vehicle communications, our study introduces a ...
Jonathan Israel, Xavier Boulanger, Vegard Arneson   +2 more
wiley   +1 more source

Whither business model innovation strategy in the age of AI?

Strategic Entrepreneurship Journal, EarlyView.
Abstract Research Summary We argue that business models are transformed into auto‐adaptive systems through embedded AI inference and learning activities. The competitive advantage of focal firms may increasingly depend on how effectively their activity systems learn relative to competing business models, with learning serving as a meta value driver ...
Christoph Zott, Raphael Amit
wiley   +1 more source

Defensive Distillation is Not Robust to Adversarial Examples

CoRR, 2016
We show that defensive distillation is not secure: it is no more resistant to targeted misclassification attacks than unprotected neural networks.
Nicholas Carlini, David A. Wagner 0001
openaire   +3 more sources

Does innovation success need advocacy? Stakeholder involvement in firm innovation

Strategic Management Journal, EarlyView.
Abstract Research Summary Prior research documents that firms often collaborate with advocacy groups to mitigate stakeholder contention. Integrating stakeholder theory into a performance model of collaborative innovation, we propose an overlooked explanation for such collaborations: to enhance the adoption of firms' innovations.
Paolo Carioli, Christoph Grimpe, Karin Hoisl, Wolfgang Sofka   +3 more
wiley   +1 more source

Quantum Machine Learning for Cybersecurity: A Taxonomy and Future Directions

Software: Practice and Experience, EarlyView.
ABSTRACT Context The rapid increase in cyber threats, coupled with increasingly sophisticated attack strategies and the exponential growth of data in recent years, has exposed significant limitations in classical machine learning, rule‐based, and signature‐based defense mechanisms.
Siva Sai, Ishika Goyal, Shubham Sharma, Sri Harshita Manuri, Vinay Chamola, Rajkumar Buyya   +5 more
wiley   +1 more source

Research Progress on Thermal Runaway and Thermal Management of Lithium‐Ion Batteries

Safety Science and Technology, EarlyView.
This review summarizes thermal runaway mechanisms, propagation pathways, mitigation strategies, and intelligent thermal management technologies for lithium‐ion batteries, highlighting the transition from passive heat dissipation to integrated safety regulation through advanced cooling, barrier materials, sensing, machine learning, and digital‐twin ...
Songrong Li, Wenjia Zhao, Yutong Zhang, Xianyong Wu, Zhongxue Chen   +4 more
wiley   +1 more source

The Reflexive Turn in Systems Engineering: A Disciplinary Response to Complexity

Systems Engineering, EarlyView.
ABSTRACT The Future of Systems Engineering (FuSE) programme has called for the discipline to evolve as a transdiscipline capable of engaging complex eco‐socio‐technical challenges. Yet the pace of that evolution has been slower than the arguments for it would predict. This article examines why.
Raul Leal Ascencio
wiley   +1 more source

Knowing is Half the Battle: Enhancing Clean Data Accuracy of Adversarial Robust Deep Neural Networks via Dual-Model Bounded Divergence Gating

IEEE Access
Significant advances have been made in recent years in improving the robustness of deep neural networks, particularly under adversarial machine learning scenarios where the data has been contaminated to fool networks into making undesirable predictions ...
Hossein Aboutalebi, Mohammad Javad Shafiee, Chi-En Amy Tai, Alexander Wong   +3 more
doaj   +1 more source

Moving target defense for adaptive adversaries

2013 IEEE International Conference on Intelligence and Security Informatics, 2013
Machine learning (ML) plays a central role in the solution of many security problems, for example enabling malicious and innocent activities to be rapidly and accurately distinguished and appropriate actions to be taken. Unfortunately, a standard assumption in ML - that the training and test data are identically distributed - is typically violated in ...
Richard Colbaugh, Kristin Glass
openaire   +2 more sources