A5034613729- Recycling and Waste Management Techniques
- Environmental Impact and Sustainability
- Sustainable Industrial Ecology
- Sustainable Supply Chain Management
- Metallurgy and Material Science
- Energy and Environmental Systems
- Environmental Policies and Emissions
- Quantum Information and Cryptography
- Quantum Computing Algorithms and Architecture
- Extraction and Separation Processes
- Hybrid Renewable Energy Systems
- Energy and Environment Impacts
- Photovoltaic Systems and Sustainability
- Environmental Sustainability in Business
- Green IT and Sustainability
- solar cell performance optimization
- Technology and Data Analysis
- Engineering Applied Research
- Catalysts for Methane Reforming
- Polymer composites and self-healing
- Agriculture, Soil, Plant Science
- Blind Source Separation Techniques
- Stochastic Gradient Optimization Techniques
- Climate Change Policy and Economics
- Integrated Energy Systems Optimization
Yonsei University
2023-2024
Konkuk University Medical Center
1998-2022
Imperial College London
2022
Konkuk University
2007-2021
Korea Institute of Industrial Technology
2012
Lehigh University
1988
Quantum computing is expected to provide exponential speedup in machine learning. However, optimizing the data loading process, commonly referred as quantum embedding, maximize classification performance remains a critical challenge. In this work, we propose neural embedding (NQE) technique based on deterministic computation with one qubit (DQC1). Unlike traditional approach, NQE trains network trace distance between states corresponding different categories of classical data. Furthermore,...
Quantum embedding is a fundamental prerequisite for applying quantum machine learning techniques to classical data and has substantial impacts on performance outcomes. In this study, we present neural (NQE), method that efficiently optimizes beyond the limitations of positive trace-preserving maps by leveraging deep-learning techniques. NQE enhances lower bound empirical risk, leading improvements in classification performance. Moreover, improves robustness against noise. To validate...
As environmental regulations have become more stringent for hazardousness and recyclability of products in WEEE, RoHS EuE, export-oriented Korean industries are showing interests ecodesign. The ecodesign system referred to as "Instep-DfE" we developed this study is subject electric electronic industries, not only cope with the regulations, but also contribute strengthening competitiveness products. Moreover, a number databases helpful search useful information needed product designers users....
In order to effectively integrate the environmental aspects into product design and development processes, it is crucial identify related a system within relatively short period of time by using appropriate assessment tools. this study, simplified LCA (SLCA) environmentally responsible matrix (ERPA) methods were evaluated usefulness as tool for identifying products in eco-design was examined. The case studies cellular phone vacuum cleaner systems showed that SLCA ERPA provided different...