Short-term Load Forecasting of Buildings based on Artificial Neural Network and Clustering Technique

Ngo, Minh-Duc,Yun, Sang-Yun,Choi, Joon-Ho,Ahn, Seon-Ju Institute of Korean Electrical and Electronics Eng 2018 전기전자학회논문지 Vol.22 No.3

Recently, microgrid (MG) has been proposed as one of the most critical solutions for various energy problems. For the optimal and economic operation of MGs, it is very important to forecast the load profile. However, it is not easy to predict the load accurately since the load in a MG is small and highly variable. In this paper, we propose an artificial neural network (ANN) based method to predict the energy use in campus buildings in short-term time series from one hour up to one week. The proposed method analyzes and extracts the features from the historical data of load and temperature to generate the prediction of future energy consumption in the building based on sparsified K-means. To evaluate the performance of the proposed approach, historical load data in hourly resolution collected from the campus buildings were used. The experimental results show that the proposed approach outperforms the conventional forecasting methods.

Short-term Load Forecasting of Buildings based on Artificial Neural Network and Clustering Technique

Minh-Duc Ngo,Sang-Yun Yun,Joon-Ho Choi,Seon-Ju Ahn 한국전기전자학회 2018 전기전자학회논문지 Vol.22 No.3

Recently, microgrid (MG) has been proposed as one of the most critical solutions for various energy problems. For the optimal and economic operation of MGs, it is very important to forecast the load profile. However, it is not easy to predict the load accurately since the load in a MG is small and highly variable. In this paper, we propose an artificial neural network (ANN) based method to predict the energy use in campus buildings in short-term time series from one hour up to one week. The proposed method analyzes and extracts the features from the historical data of load and temperature to generate the prediction of future energy consumption in the building based on sparsified K-means. To evaluate the performance of the proposed approach, historical load data in hourly resolution collected from the campus buildings were used. The experimental results show that the proposed approach outperforms the conventional forecasting methods.

The Role of Economics, Politics and Institutions on Budget Deficit in ASEAN Countries

NGO, Minh Ngoc,NGUYEN, Loc Duc Korea Distribution Science Association 2020 The Journal of Asian Finance, Economics and Busine Vol.7 No.9

The paper examines the role of some determinants of economics, politics and institutions on the budget deficit volatility in some countries of the Association of South East Asian Nations (ASEAN) such as Indonesia, Thailand and Vietnam. The paper uses the fixed effects model (FEM) and the random effects model (REM) to investigate panel data of these countries in the period of 1990-2018. Moreover, the study also explores ordinary least square (OLS) to analyze time-series data for each country in the same period to make comparison among them. The economic data is collected from international financial statistics and world development indicators. The data on political variables are collected from International Country Risk Data Guide (ICRG). The empirical results both confirm that corruption and political stability are important indicators of budget deficit. Besides, the paper suggests authorities should pay more attention on improving the institutional setup of the economy in order to avoid high and unstable deficit. The findings offer new insight on the budget deficit in essence and suggest that the most important thing need to be done ahead is to strongly implement anti-corruption actions. By doing so, the status of budget deficit would be remarkably improved immediately.

Data Envelopment Analysis on Measuring the Performance of Vietnamese Joint-Stock Commercial Banks

NGO, Duc Tien,PHUNG, Thu Ha,DINH, Tuan Minh,NGUYEN, Thuy Lien Korea Distribution Science Association 2022 The Journal of Asian Finance, Economics and Busine Vol.9 No.7

Commercial banks have a significant impact on the economy of Vietnam because they provide the majority of transactional capital. Therefore, the operational efficiency of commercial banks is a viral topic for the study of the Vietnamese banking system. The research aims to examine the efficiency and inefficiency of joint-stock commercial banks in Vietnam from 2016 to 2020 and then classify them into the efficient group and inefficient group. The study employs the time series data of 29 joint-stock commercial banks during the period 2016-2020. Based on the data collected from the annual audited financial statements of 29 Vietnamese joint-stock commercial banks, the authors select input and output variables for the standard DEA models and anti-efficient DEA models. This research uses two stages, first, by applying the standard DEA model, we investigate the efficient banks; second, by employing the anti-efficient DEA model, we find out the inefficient banks. The results reveal that the average efficiency score of 29 joint-stock commercial banks tends to increase in the period 2016-2018 and decrease gradually in the period 2019-2020. The findings of this study suggest that several small and medium-sized banks in the Vietnamese banking sector have both promising and risky performances and the efficiency of state-owned commercial banks has also improved significantly during the study period.

Economic Growth, Total Factor Productivity, and Institution Quality in Low-Middle Income Countries in Asia

NGO, Minh Ngoc,NGUYEN, Loc Duc Korea Distribution Science Association 2020 The Journal of Asian Finance, Economics and Busine Vol.7 No.7

The purpose of this paper is to investigate the impact of total factor productivity (TFP), institutional quality, and interactive variable between them on economic growth in 13 low-middle income countries in Asia for the period 2000-2018. The paper uses the difference Generalized Method of Moments (GMM) to explore the dataset provided by the World Bank. The empirical results show that TFP and the interactive variable positively impact on the economic growth, while the institutional determinants have a negative influence. The negative effect is explained by the weak institutions in these low-middle income countries. The findings of the study suggest two points. First, the government should continue to improve TFP, which is associated with the application of technical advances, technological innovations, improvement of management methods, and skilled workers. Second, far more important, is that the authorities should pay special attention to implement institutional reform and strengthen the governance in the future. The successful experiences from Japan, Korea and Singapore will help other governments in Asian low-middle income countries to build developmental state. Probably, the developmental state actively interfere in the market to promote and realize the development goals. By doing so, these economies might overcome the so-called "middle-income trap".

Carbon-Nanotube Growth over Iron Nanoparticles Formed on CaCO3 Support by Using Hydrogen Reduction

Nguyen Duc Dung,Nguyen Van Chuc,Ngo Thi Thanh Tam,Nguyen Hong Quang,Phan Hong Khoi,Phan Ngoc Minh 한국물리학회 2008 THE JOURNAL OF THE KOREAN PHYSICAL SOCIETY Vol.52 No.5

Carbon nanotubes (CNTs) were grown by chemical vapor deposition on a mixture of iron salt and CaCO3. Salt mixtures of Fe(NO₃)₃9H₂O/CaCO₃ and FeCl₃6H₂O/CaCO₃ with various Fe weight contents were used as catalysts for growing the CNTs. A scanning electron microscope study revealed that the CNTs were densely grown on the Fe(NO₃)₃9H₂O/CaCO₃ catalyst containing 5 wt.% Fe. The effect of growth temperature on the segregation of Fe nanoparticles formed by hydrogen reduction is discussed. The result shows that 800 ℃ is the optimal temperature for the formation of Fe nanoparticles over which CNTs grow with the highest yield of 78.61 %. A raman spectroscope and a scanning transmission electron microscope were utilized to characterize the multiwall structure of the CNTs. The 92.16 % purity of the CNTs was determined by using thermal gravimetric analysis. Carbon nanotubes (CNTs) were grown by chemical vapor deposition on a mixture of iron salt and CaCO3. Salt mixtures of Fe(NO₃)₃9H₂O/CaCO₃ and FeCl₃6H₂O/CaCO₃ with various Fe weight contents were used as catalysts for growing the CNTs. A scanning electron microscope study revealed that the CNTs were densely grown on the Fe(NO₃)₃9H₂O/CaCO₃ catalyst containing 5 wt.% Fe. The effect of growth temperature on the segregation of Fe nanoparticles formed by hydrogen reduction is discussed. The result shows that 800 ℃ is the optimal temperature for the formation of Fe nanoparticles over which CNTs grow with the highest yield of 78.61 %. A raman spectroscope and a scanning transmission electron microscope were utilized to characterize the multiwall structure of the CNTs. The 92.16 % purity of the CNTs was determined by using thermal gravimetric analysis.

Effective Elimination of Charge-associated Toxicity of Low Generation Polyamidoamine Dendrimer Eases Drug Delivery of Oxaliplatin

Vo Minh Hoang Do,Long Giang Bach,Diem-Huong Nguyen Tran,Van Du Cao,Thi Nhu Quynh Nguyen,Duc Thuan Hoang,Van Cuong Ngo,Dai Hai Nguyen,Thai Thanh Hoang Thi 한국생물공학회 2020 Biotechnology and Bioprocess Engineering Vol.25 No.2

Polyamidoamine (PAMAM) dendrimer is emerging as an effective nanocarrier for delivering anticancer drugs. Still, unmodified PAMAM dendrimer is hardly used in vivo because of unsatisfied drug release, high tendency of interfering with cellular membranes, and rapid clearance by reticuloendothelial system. In this study, low generation polyamidoamine (PAMAM) dendrimer G3.0 is developed and surface modified with methoxypolyethylene glycol (PAMAM G3.0-mPEG) to overcome its limitations. Specifically, PAMAM G3.0 conjugated with mPEG at different ratios are investigated to effectively eliminate its charge-associated toxicity, in which PAMAM G3.0-mPEG- 8 is chosen for oxaliplatin (OX) loading. Results reveal that OX-loaded PAMAM G3.0-mPEG-8 has desirable size, good entrapment efficiency, and sustained release with minimum drug leakage. In addition, Resazurin assay indicates that the toxicity of loaded OX is reduced as compared to free drug but still maintain substantially anticancer activity on HeLa cells, suggesting the potential application of PAMAM G3.0-mPEG-8 for OX delivery in cancer therapy.

Dry semi-continuous anaerobic digestion of food waste in the mesophilic and thermophilic modes: New aspects of sustainable management and energy recovery in South Korea

Nguyen, Dinh Duc,Chang, Soon Woong,Cha, Jae Hun,Jeong, Seong Yeob,Yoon, Yong Soo,Lee, Sin Jin,Tran, Minh Chi,Ngo, Huu Hao Elsevier 2017 Energy conversion and management Vol.135 No.-

<P><B>Abstract</B></P> <P>In this study, parallel, bench-scale, mesophilic and thermophilic, dry, semi-continuous anaerobic digestion (DScAD) of Korea food waste (FW, containing 22% total solids (TS) and 20% volatile solids (VS)) was investigated thoroughly under varying operational conditions, including hydraulic retention times (HRTs) and organic loading rates (OLRs). The aim was to evaluate the start-up, stability, overall removal efficiency, and inhibitory effects of toxic compounds on process performance over a long-term operation lasting 100days. The results from both digesters indicate that the simultaneous reduction of VS and the production of gas improved as the HRT decreased or the OLR increased. The highest average rates of VS reduction (79.67%) and biogas production (162.14m<SUP>3</SUP> biogas/ton of FW, 61.89% CH<SUB>4</SUB>), at an OLR of 8.62±0.34kgVS/m<SUP>3</SUP> day (25days of HRT), were achieved under thermophilic DScAD. In addition, the average rates of reduction of VS and the production of biogas in thermophilic DScAD were higher by 6.88% and 16.4%, respectively, than were those in mesophilic DScAD. The inhibitory effects of ammonia, H<SUB>2</SUB>S, and volatile fatty acids (VFAs) on methane production was not clear from either of the digesters, although, apparently, their concentrations did fluctuate. This fluctuation could be attributed to the self-adaptation of the microbial well. However, digestion that was more stable and faster was observed under thermophilic conditions compared with that under mesophilic conditions. Based on our results, the optimum operational parameters to improve FW treatment and achieve higher energy yields could be determined, expanding the application of DScAD in treating organic wastes.</P> <P><B>Highlights</B></P> <P> <UL> <LI> DScAD remained stable even at a high rate of organic loading. </LI> <LI> Higher OLR led to the more reduction of VS and the production of biogas. </LI> <LI> Thermophilic digesters had higher reduction of VS and the generation of biogas. </LI> <LI> Stable with faster digestion and higher OLR was achieved in the thermophilic operation. </LI> <LI> Acetic and propionic acids were the most prominent in the TVFA. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>

Effect of soybean oil as a carbon source on the electrochemical property of LiNi1/3Co1/3Mn1/3O2 cathode material for lithium ion battery

Nguyen Van Hiep,Ngo Minh Duc,김영호 한국탄소학회 2020 Carbon Letters Vol.30 No.6

In this study, soybean oil, which is used in a large variety of processed foods, is used as a carbon source. Soybean oil is successfully coated onto the surface of LiNi1/3Co1/3Mn1/3O2 (NCM) by a simple method. The physical and electrochemical properties of NCM/C hybrid materials are determined. As a result, a 5 nm thickness carbon coating layer is formed on the surface of the NCM, resulting in improved capability and cyclic performance in the battery. The NCM/C battery shows an initial discharge capacity of 159 mAh g−1 and 95% capacity retention after 100 cycles (a discharge capacity of 120 mAh g−1 and 94% retention are observed after 100 cycles for the NCM cathode).

Adaptive Control for Uncertain Model of Omni-directional Mobile Robot Based on Radial Basis Function Neural Network

Duyen Ha Thi Kim,Tien Ngo Manh,Cuong Nguyen Manh,Nhan Duc Nguyen,Dung Pham Tien,Manh Tran Van,Minh Phan Xuan 제어·로봇·시스템학회 2021 International Journal of Control, Automation, and Vol.19 No.4

The paper proposes the method to deal with control problems of unmodeled components of the fourwheeled Omni-directional mobile robot. It is commonly challenging to design a model-based control scheme to achieve smooth movement in the tracking process due to the unknown elements in the mathematical model of the robot or external disturbances. Our main contribution focuses on designing an adaptive controller based on neural networks with online weight updating laws and Fuzzy logic to guarantee the high accuracy of the robot’s movement when the unknown factors adversely affect the robot control. At the initial step, a Dynamic Surface Control plays a role as a core of the controller for the robot system. Then, with the ability to estimate the appropriate value for uncertain nonlinear parts, a Radial Basis Function Neural Network is designed. Finally, a Fuzzy law is to utilize control parameters in each period to increase the adaptive behavior of the system. The stability and convergence of the system are proven by the Lyapunov’s stability theory. The simulation results illustrate the validity and the efficiency of the proposed control algorithm when the system is lack of robot model’s information.