• Journal of Power Electronics
• /
• v.16 no.6
• /
• pp.2231-2242
• /
• 2016

A simplified model predictive control method is presented in this paper. This method is based on a future reference voltage vector for a three-phase four-leg voltage source inverter (VSI). Compared with the three-leg VSIs, the four-leg VSI increases the possible switching states from 8 to 16 owing to a fourth leg. Among the possible states, this should be considered in the model predictive control method for selecting an optimal state. The increased number of candidate switching states and the corresponding voltage vectors increase the calculation burden. The proposed technique can preselect 5 among the 16 possible voltage vectors produced by the three-phase four-leg voltage source inverters, based on the position of the future reference voltage vector. The discrete-time model of the future reference voltage vector is built to predict the future movement of the load currents, and its position is used to choose five preselected vectors at every sampling period. As a result, the proposed method can reduce calculation load by decreasing the candidate voltage vectors used in the cost function for the four-leg VSIs, while exhibiting the same performance as the conventional method. The effectiveness of the proposed method is demonstrated with simulation and experiment results.

• Journal of Information Processing Systems
• /
• v.17 no.1
• /
• pp.14-27
• /
• 2021

Strong earthquakes have caused substantial losses in recent years, and earthquake risk prevention has aroused a significant amount of attention. Earthquake risk prevention products can help improve the self and mutual-rescue abilities of people, and can create convenient conditions for earthquake relief and reconstruction work. At present, it is difficult for earthquake risk prevention information systems to meet the information requirements of multiple scenarios, as they are highly specialized. Aiming at mitigating this shortcoming, this study investigates and analyzes four user roles (government users, public users, social force users, insurance market users), and summarizes their requirements for earthquake risk prevention products in the whole disaster chain, which comprises three scenarios (pre-quake preparedness, in-quake warning, and post-quake relief). A targeted recommendation rule base is then constructed based on the case analysis method. Considering the user's location, the earthquake magnitude, and the time that has passed since the earthquake occurred, a targeted recommendation model is built. Finally, an Android APP is implemented to realize the developed model. The APP can recommend multi-form earthquake risk prevention products to users according to their requirements under the three scenarios. Taking the 2019 Lushan earthquake as an example, the APP exhibits that the model can transfer real-time information to everyone to reduce the damage caused by an earthquake.

• International Journal of Computer Science & Network Security
• /
• v.22 no.6
• /
• pp.319-331
• /
• 2022

The latest global COVID-19 pandemic has made the use of facial masks an important aspect of our lives. People are advised to cover their faces in public spaces to discourage illness from spreading. Using these face masks posed a significant concern about the exactness of the face identification method used to search and unlock telephones at the school/office. Many companies have already built the requisite data in-house to incorporate such a scheme, using face recognition as an authentication. Unfortunately, veiled faces hinder the detection and acknowledgment of these facial identity schemes and seek to invalidate the internal data collection. Biometric systems that use the face as authentication cause problems with detection or recognition (face or persons). In this research, a novel model has been developed to detect and recognize faces and persons for authentication using scale invariant features (SIFT) for the whole segmented face with an efficient local binary texture features (DLBP) in region of eyes in the masked face. The Fuzzy C means is utilized to segment the image. These mixed features are trained significantly in a convolution neural network (CNN) model. The main advantage of this model is that can detect and recognizing faces by assigning weights to the selected features aimed to grant or provoke permissions with high accuracy.

• Journal of Distribution Science
• /
• v.20 no.6
• /
• pp.75-86
• /
• 2022

Purpose: This research aims to provide empirical evidence on the impact of digital literacy on behavioural intention regarding using technology for distribution of higher education. Design, Methodology, and Approach: Quantitative analysis was carried out using Covariance-Based Structural Equation Model with data collected from 901 students who fully experienced 2-year study online at different universities in Vietnam. The structural model was built with digital literacy as the primary indicator and other variables were included based on modified version of Unified Theory of Acceptance and Use of Technology (UTAUT2) by adopting performance expectancy, effort expectancy, social influence, habit, and hedonic motivation variables specifically for education sector. Self-efficacy was added to eliminate possible bias in technology acceptance. Results: From the results of model estimation, digital literacy presented positive impact on the online distribution of higher education in Vietnam. The mediating effects of various indicators such as performance expectancy, effort expectancy, social influence, habit, hedonic motivation, and self-efficacy are significantly determined by research model. Conclusion: The higher level of digital literacy of the students, the more likely that they will use technology in higher education study, especially online learning. Additionally, the mediating effects of indicators from the UTAUT2 theoretical model were also evident to be positively significant.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.18 no.5
• /
• pp.203-208
• /
• 2023

Recently, with the growing interest in the field of autonomous driving, many researchers have been focusing on developing autonomous driving software platforms. In particular, we have concentrated on developing 3D object detection models that can improve real-time performance. In this paper, we introduce a self-constructed 3D LiDAR dataset specific to domestic environments and propose a VariFocal-based CenterPoint for the 3D object detection model, with improved performance over the previous models. Furthermore, we present experimental results comparing the performance of the 3D object detection modules using our self-built and public dataset. As the results show, our model, which was trained on a large amount of self-constructed dataset, successfully solves the issue of failing to detect large vehicles and small objects such as motorcycles and pedestrians, which the previous models had difficulty detecting. Consequently, the proposed model shows a performance improvement of about 1.0 mAP over the previous model.

• Knowledge Management Research
• /
• v.22 no.2
• /
• pp.19-32
• /
• 2021

Bitcoin, a representative cryptocurrency, is receiving a lot of attention around the world, and the price of Bitcoin shows high volatility. High volatility is a risk factor for investors and causes social problems caused by reckless investment. Since the price of Bitcoin responds quickly to changes in the world environment, we propose to predict the price volatility of Bitcoin by utilizing news information that provides a variety of information in real-time. In other words, positive news stimulates investor sentiment and negative news weakens investor sentiment. Therefore, in this study, sentiment information of news and deep learning were applied to predict the change in Bitcoin yield. A single predictive model of logit, artificial neural network, SVM, and LSTM was built, and an integrated model was proposed as a method to improve predictive performance. As a result of comparing the performance of the prediction model built on the historical price information and the prediction model reflecting the sentiment information of the news, it was found that the integrated model based on the sentiment information of the news was the best. This study will be able to prevent reckless investment and provide useful information to investors to make wise investments through a predictive model.

• Asia pacific journal of information systems
• /
• v.10 no.3
• /
• pp.105-120
• /
• 2000

The objective of this paper is to show how team study can be advanced with the aid of a current computer technology, that is distributed Artificial Intelligence(DAI). Studying distributed problem solving by using groups of artificial agents, DAI can provide important ideas and techniques for the study of team behaviors like team decision making. To demonstrate the usefulness of DAI models as team research tools, a DAI model called 'Team-Soar' was built and a simulation experiment done with the model was introduced, Here, Team-Soar models a naval command and control team consisting of four members whose mission was to identify the threat level of aircraft. The simulation experiment was performed to examine the relationships of team decision scheme and member incompetence with team performance. Generally, the results of the Team-Soar simulation met expectations and confirmed previous findings in the literature. For example, the results support the existence of main and interaction effects of team decision scheme and member competence on team performance. Certain results of the Team-Soar simulation provide new insights about team decision making, which can be tested against human subjects or empirical data.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.19 no.4
• /
• pp.47-53
• /
• 2011

Firstly, FEM model for the body frame of a fuel cell vehicle was built up and design optimization results based on different schemes were exhibited. One scheme was to minimize weight while maintaining the normal mode frequencies and the other was to increase the frequencies without weight change. Next, for a rear frame model, shape parameter study on collapse characteristics such as peak resistance load and absorbed energy was carried out. Also, the stiffness of frame mounting brackets was predicted using inertance calculation and the durability of those mounting brackets for vehicle system loads was evaluated. Finally, for a representative mounting model, the influence on durability due to thickness change was analyzed.

• Proceedings of the Korea Concrete Institute Conference
• /
• 2002.05a
• /
• pp.849-854
• /
• 2002

From the analysis results of some as-built drawings in national roadway bridges in Korea, many bridge piers are expected to show complex shear-flexural behaviour under earthquakes. But the previous research works about the seismic evaluation of bridges considered flexural behaviour RC piers only. In addition, the past bridge design specifications in Korea didn't include limitation on the amount of longitudinal lap splices in the plastic hinge zone of piers. Thus a large majority of non-seismically designed bridge piers in Korea may have lap splices in plastic hinge zone. In this study, prototype pier was selected among existent bridge piers whose failure mode is expected to be complex shear-flexural mode. And then, full scale and 1/2 reduced scale model RC piers with various longitudinal lap splice details were constructed. From the quasi static test results on these model RC piers, the effect of longitudinal lap splices on the seismic performance of bridges piers was analyzed. And the seismic capacity of the non-seismically designed shear-flexural RC piers was evaluated.

• Journal of The Korea Institute of Healthcare Architecture
• /
• v.9 no.1
• /
• pp.43-51
• /
• 2003

The purpose of this study is to find out the design guideline for women's hospital focusing on the patient needs. This study is performed the literature review of the performance evaluation & spatial satisfaction. And then, the spatial characteristics of selected women's hospitals, which were recently built in Korea, were analyzed. This study is suggested in the spatial satisfaction evaluation model in order to the spatial evaluation performance elements of the patient needs. The evaluation model of space efficiency derived from this study is expected to be used for the actual guide to architecture of women's hospitals as substantial materials. Finally, the model is used to for the planning & design for the future women's hospital.