• Journal of Power Electronics
• /
• v.19 no.5
• /
• pp.1087-1098
• /
• 2019

In this paper, a detuning factor (DeFac) method is proposed to design the key parameters for optimizing the transfer power and efficiency of an Inductively Coupled Power Transfer (ICPT) system with primary-secondary side compensation. Depending on the robustness of the system, the DeFac method can guarantee the stability of the transfer power and efficiency of an ICPT system within a certain range of resistive-capacitive or resistive-inductive loads. A MATLAB-Simulink model of a ICPT system was built to assess the system's main evaluation criteria, namely its maximum power ratio (PR) and efficiency, in terms of different approaches. In addition, a magnetic field simulation model was built using Ansoft to specify the leakage flux and current density. Simulation results show that both the maximum PR and efficiency of the ICPT system can reach almost 70% despite the severe detuning imposed by the DeFac method. The system also exhibited low levels of leakage flux and a high current density. Experimental results confirmed the validity and feasibility of an ICPT system using DeFac-designed parameters.

• Journal of the Korean Ceramic Society
• /
• v.56 no.1
• /
• pp.65-70
• /
• 2019

Simple fabrication of a powdered Ge-reduced graphene oxide (Ge-rGO) composite via spray pyrolysis and reduction is introduced herein. Successful incorporation of the rGO nanosheets with Ge hindered the aggregation of Ge and conferred enhanced structural stability to the composite by alleviating the mechanical stress associated with drastic volume changes during repeated cycling. The Li-ion storage performance of Ge-rGO was compared with that of powdered Ge metal. The reversible discharge capacity of Ge-rGO at the $200^{th}$ cycle was $748mA\;h\;g^{-1}$ at a current density of $1.0A\;g^{-1}$ and Ge-rGO showed a capacity of $375mA\;h\;g^{-1}$ even at a high current density of $5.0A\;g^{-1}$. The excellent performance of Ge-rGO is attributed to the structural robustness, enhanced electrical conductivity, and formation of open channels between the rGO nanosheets, which facilitated electrolyte penetration for improved Li-ion diffusion.

• Journal of the Korean Society of Systems Engineering
• /
• v.14 no.2
• /
• pp.58-66
• /
• 2018

This paper represents a systematic approach aimed at improving the performance of the proportional integral (PI) controller for the Advanced Power Reactor (APR) 1400 Feedwater Control System (FWCS). When the performance of the PI controller offers superior control and enhanced robustness, the steam generator (SG) level is properly controlled. This leads to the safe operation and increased the availability of the nuclear power plant. In this paper, a systems engineering approach is used in order to design a novel PI controller for the FWCS. In the reverse engineering stage, the existing FWCS configuration, especially the characteristics of the feedwater controller as well as the feedwater flow path to each SG from the FWCS, were reviewed and analysed. The overall block diagram of the FWCS and the SG was also developed in the reverse engineering process. In the re-engineering stage, the actual design of the feedwater PI controller was carried out using a genetic algorithm (GA). Lastly, in the validation and verification phase, the existing PI controller and the PI controller designed using GA method were simulated in Simulink/Matlab. From the simulation results, the GA-PI controller was found to exhibit greater stability than the current controller of the FWCS.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.9
• /
• pp.3258-3273
• /
• 2021

Malware is a severe threat to the computing system and there's a long history of the battle between malware detection and anti-detection. Most traditional detection methods are based on static analysis with signature matching and dynamic analysis methods that are focused on sensitive behaviors. However, the usual detections have only limited effect when meeting the development of malware, so that the manual update for feature sets is essential. Besides, most of these methods match target samples with the usual feature database, which ignored the characteristics of the sample itself. In this paper, we propose a new malware detection method that could combine the features of a single sample and the general features of malware. Firstly, a structure of Directed Cyclic Graph (DCG) is adopted to extract features from samples. Then the sensitivity of each API call is computed with Markov Chain. Afterward, the graph is merged with the chain to get the final features. Finally, the detectors based on machine learning or deep learning are devised for identification. To evaluate the effect and robustness of our approach, several experiments were adopted. The results showed that the proposed method had a good performance in most tests, and the approach also had stability with the development and growth of malware.

• Journal of Auto-vehicle Safety Association
• /
• v.13 no.3
• /
• pp.32-40
• /
• 2021

Composite material is very attractive because it has excellent mechanical property and is possible to lightweight due to the low density. However, composite material is less used compared to other systems in the chassis system because it is very hard to solve NVH problem when composite material is applied to vehicle. Especially, reducing squeal noise of composite brake system is essential to apply it to vehicle successfully. In this paper, we present a new solution to reduce squeal noise of composite brake system. To achieve this goal, we analyze main causes of noise using RCA (Root Cause Analysis), CA (Contradiction Analysis) and sequentially get IFR (Ideal Final Result) to solve the problem. Next, we define the function of composite brake system and derive control factors and noise factors. A variety of tests for factors like chamfer, slot, damping shim, underlayer of brake pad are done. In addition, we analyze level of contribution for control factors theoretically. Finally, we get the effective solution for reducing squeal noise.

• Journal of Power Electronics
• /
• v.19 no.6
• /
• pp.1527-1535
• /
• 2019

Because of the shortcomings of the PID controllers and traditional drive systems of permanent magnet synchronous motors (PMSMs), a PMSM passivity-based control (PBC) drive system based on a quasi-Z source matrix converter (QZMC) is proposed in this paper. The traditional matrix converter is a buck converter with a maximum voltage transmission ratio of only 0.866, which limits the performance of the driven motor. Therefore, in this paper a quasi-Z source circuit is added to the input side of the two-stage matrix converter (TSMC) and its working principle has also been verified. In addition, the controller of the speed loop and current loop in the conventional vector control of a PMSM is a PID controller. The PID controller has the problem since its parameters are difficult to adjust and its anti-interference capability is limited. As a result, a port controlled dissipative Hamiltonian model (PCHD) of a PMSM is established. Thereafter a passivity-based controller based on the interconnection and damping assignment (IDA) of a QZMC-PMSM is designed, and the stability of the equilibrium point is theoretically verified. Simulation and experimental results show that the designed PBC control system of a PMSM based on a QZMC can make the PMSM run stably at the rated speed. In addition, the system has strong robustness, as well as good dynamic and static performances.

• Asia-Pacific Journal of Business
• /
• v.11 no.2
• /
• pp.27-43
• /
• 2020

Purpose - This study explores the impact of the real estate industry on related industries for the perspective of Chinese steel companies. Design/methodology/approach - The impact of housing prices on the 41 listed steel companies' performance was analyzed by using the panel data model. We used two kinds of housing price indexes that are set in the panel data models to estimate the range of the real estate market, driving the performance growth of steel listed companies. Moreover, the net profit of steel companies is used as the dependent variable. To test the stability of the model, ROA used as a dependent variable for the robustness test. Also, to avoid the time trend of housing prices, this paper selects the growth rate of housing prices as the primary research variable. After Fisher-type testings, there is no unit root problem in both independent and dependent variables. Findings - The results indicated that the rise in the housing price has a positive influence on the steel company performance. When the housing price increases by 1%, the net profit of steel enterprises will increase by 5 to 20 million yuan. Research implications or Originality - In this paper, empirical data at the micro-level and panel model are used to quantify China's real estate industry's driving effect on the iron and steel industry, providing evidence from the microdata level. It helps us to understand further the status and role of China's real estate industry in the economic structure.

• Journal of Information Technology Services
• /
• v.20 no.5
• /
• pp.177-187
• /
• 2021

The global economy has been very difficult due to the recent impact of COVID-19. Korea is also pushing for strong quarantine policies such as K- quarantine and social distancing, but the economy is hardly recovering. In particular, the economic situation began to change rapidly depending on the export and domestic market, the public's interest in the economy increased, and companies became more sensitive. In order to estimate this rapidly changing economic situation, major advanced countries have also developed models that can periodically monitor the economy at the government level. Through this, by periodically reporting the economic trends, the public and companies can be aware of the economic trends to some extent. This study analyzed the cases of weekly business trends in advanced countries and developed a model of weekly economic activity suitable for Korea. To verify this, indices closely related to the economy such as mobility, industrial activity, face-to-face consumption, and psychology were discovered and estimated. As a result of the study, the weekly economic activity index was judged to be very useful in capturing short-term real economic activity. In the future, in order to secure the robustness and stability of the index and to increase the reflection of reality, model improvement and parameter estimation should be performed regularly.

• International Journal of Computer Science & Network Security
• /
• v.24 no.3
• /
• pp.1-11
• /
• 2024

Payment systems are evolving, and this study examines how blockchain and AI improve online transactional security and service quality. The study examines micro and macro payment systems, compares online, and offline methods all over the world. The study also examines how blockchain and AI affect payment system security, privacy, and efficiency globally and rapidly digitizing economy. Digital payment methods are growing all over the world with high literacy and digital engagement, but they face challenges. The research highlights cybersecurity threats and the need to balance user convenience and security. It suggests blockchain and AI improve online payment services, supporting the policies for different countries. In this extensive research survey, we compare and evaluate the strengths and weaknesses of various payment systems, their practicality, and their robustness. This study also examines how technological innovations and payment systems interact to reveal how blockchain and AI could transform the financial sector. It seeks to understand how technology-enhancing service quality can boost customer satisfaction and financial stability in the digital age. The findings should help policymakers, financial institutions, and technology developers optimize online payment systems for a more secure and efficient digital economy.

• The Journal of Korea Robotics Society
• /
• v.19 no.2
• /
• pp.139-148
• /
• 2024

In this paper, we propose a two-degree-of-freedom snake robot head system and an I-PID (Intelligent Proportional-Integral-Derivative)-based controller utilizing RBF (Radial Basis Function) neural network and adaptive robust terms as a control strategy to reduce rotation occurring in the snake robot head. This study proposes a two-degree-of-freedom snake robot head system to avoid complex snake robot dynamics. This system has a control system independent of the snake robot. Subsequently, it utilizes an I-PID controller to implement a control system that can effectively manage rotation at the snake robot head, the robot's nonlinearity, and disturbances. To compensate for the time delay estimation errors occurring in the I-PID control system, an RBF neural network is integrated. Additionally, an adaptive robust term is designed and integrated into the control system to enhance robustness and generate control inputs responsive to signal changes. The proposed controller satisfies stability according to Lyapunov's theory. The proposed control strategy was tested using a 9-degreeof-freedom snake robot. It demonstrates the capability to reduce rotation in Lateral undulation, Rectilinear, and Sidewinding locomotion.