Sun‐Hee Kim

Countries around the world are expanding their investment in the new and renewable energy industry for strengthening energy security, improving air pollution, responding to climate change, and tackling energy poverty. In Korea, with the nuclear phase-out declaration in 2017, the government has announced a policy to expand the ratio of new and renewable energy from 4.7% to 20% by 2030. This study examines a floating photovoltaic power generation system, which is a new and renewable energy source.

Emotional awareness perception is a largely growing field that allows for more natural interactions between people and machines. Electroencephalography (EEG) has emerged as a convenient way to measure and track a user's emotional state. The non-linear characteristic of the EEG signal produces a high-dimensional feature vector resulting in high computational cost. In this paper, characteristics of multiple neural networks are combined using Deep Feature Clustering (DFC) to select high-quality att

In expressive arts therapy, visual art, movement, music, poetry, and creative writing offer clients opportunities to explore their hidden feelings expressed in the art forms. The colors, lines, motions, or sounds expressed during the therapy session promote better understanding of the self with support of the therapist. It is crucial to have a creative connection, not only between the self and its inner world but also between the client and the therapist for the healing process to unfold. This a

With recent advancements in artificial intelligence technologies and human–computer interaction, strategies to identify the inner emotional states of humans through physiological signals such as electroencephalography (EEG) have been actively investigated and applied in various fields. Thus, there is an increasing demand for emotion analysis and recognition via EEG signals in real time. In this paper, we proposed a new framework, emotion Recognition-Assisted Deep learning Framework from eeg sign

An electroencephalogram (EEG) is the most extensively used physiological signal in emotion recognition using biometric data. However, these EEG data are difficult to analyze, because of their anomalous characteristic where statistical elements vary according to time as well as spatial-temporal correlations. Therefore, new methods that can clearly distinguish emotional states in EEG data are required. In this paper, we propose a new emotion recognition method, named AsEmo. The proposed method ext

The adsorption of triethylenediamine (TEDA) at 300 K is observed to occur via hydrogen bonding to isolated Al-OH groups on the surface of partially dehydroxylated high area gamma-Al(2)O(3) powder. This form of bonding results in +0.3 to +0.4% blue shifts in the CH(2) scissor modes at 1455 cm(-1) and a -0.4% red shift in the CN skeletal mode at 1060 cm(-1), compared to the gas-phase frequencies. Other modes are red shifted less than 0.1%. The isolated OH modes are red shifted by -200 to -1000 cm(

In the Republic of Korea, efficient biogas-fuelled power systems are needed to use the excess biogas that is currently burned due to a lack of suitable power technology. We examined the performance of a biogas-fuelled micro-gas turbine (MGT) system and a bottoming organic Rankine cycle (ORC). The MGT provides robust operation with low-grade biogas, and the exhaust can be used for heating the biodigester. Similarly, the bottoming ORC generates additional power output with the exhaust gas. We sele

The hydrogen bonding of the triethylenediamine (TEDA) molecule to isolated Al-OH groups on partially dehydroxylated high area gamma-Al(2)O(3) powder has been studied using transmission IR spectroscopy. It has been found that TEDA adsorbs both singly and as multiple species to single Al-OH groups in clearly separable equilibrium stages of adsorption at 300 K. The reversible adsorption of a single TEDA molecule to Al-OH fits the Langmuir adsorption isotherm well, and the enthalpy of adsorption is

Model parameters' estimation is one of the most important tasks in the analysis and design process of a nonlinear dynamic system in real time, especially in the presence of noise. This article presents a novel approach in estimating important parameters of gray-box model for such a system on real nonlinear EEG to simulate efficiently the dynamic characteristics of neurons. Specifically, the proposed methodology exploits unscented Kalman filter (UKF) that is combined with chaos neural population

대부분의 에너지는 전세계적으로 제한되어 있는 석유, 석탄, 천연가스 등 주로 화석연료로부터 얻어지고 있다. 최근, 고유가, 석유자원의 고갈, 기후변화 등이 신재생에너지를 포함한 비화석 연료가 세계적으로 주목을 받고 있는 이유 중의 하나이다. 이 연구에서는 고비강성 및 비강도, 고내부식성 및 내화학성 등을 장점으로 갖고 있는 펄트루젼 FRP(PFRP)를 사용하였다. 따라서 부유식 구조물의 설계와 시공을 위해서는 PFRP 재료가 우선적으로 선택될 수 있다. 추적식 수상 태양광발전 구조물의 설계는 유한요소해석 결과를 사용하여 수행되었으며, 구조물은 조립되어 수상에 설치되었다. 구조물을 설치하기 전에 안전성 문제를 유한요소법을 사용하여 검토하였으며, 그 결과 설계, 제작, 시공된 구조물은 외적으로 작용된 하중을 지지하는데 충분히 안전함을 알 수 있었다. Most of energy are obtained from oil, coal, and natural gas, most likely, fos

Recently, wireless charging technologies for large moving objects, such as electric vehicles and robots, have been actively researched. The power transmitting and receiving coils in most large moving objects are structurally separated by a given distance, which exposes a high output power to the outside world. If a foreign metal object enters the area between these two coils during wireless power transfer, fire hazards or equipment damage may occur. Therefore, we propose a method for detecting f