• Advances in robotics research
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• v.1 no.1
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• pp.101-126
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• 2014

In this article we present modular neural control for a leg-wheel hybrid robot consisting of three legs with omnidirectional wheels. This neural control has four main modules having their functional origin in biological neural systems. A minimal recurrent control (MRC) module is for sensory signal processing and state memorization. Its outputs drive two front wheels while the rear wheel is controlled through a velocity regulating network (VRN) module. In parallel, a neural oscillator network module serves as a central pattern generator (CPG) controls leg movements for sidestepping. Stepping directions are achieved by a phase switching network (PSN) module. The combination of these modules generates various locomotion patterns and a reactive obstacle avoidance behavior. The behavior is driven by sensor inputs, to which additional neural preprocessing networks are applied. The complete neural circuitry is developed and tested using a physics simulation environment. This study verifies that the neural modules can serve a general purpose regardless of the robot's specific embodiment. We also believe that our neural modules can be important components for locomotion generation in other complex robotic systems or they can serve as useful modules for other module-based neural control applications.

• Journal of Magnetics
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• v.12 no.1
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• pp.35-39
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• 2007

A highly sensitive magnetic sensor using the Giant MagnetoImpedance effect has been developed. The sensor performance is studied and estimated. The sensor circuitry consists of a square wave generator (driving source), a sensing element in a form of composite wire of a 25 $\mu$m copper core electrodeposited with a thin layer of soft magnetic material ($Ni_{80}Fe_{20}$), and two amplifier stages for improving the gain, switching mechanism, scaler circuit, an AC power source driving the permeability of the magnetic coating layer of the sensing element into a dynamic state, and a signal pickup LC circuit formed by a pickup coil and an capacitor. Experimental studies on sensor have been carried out to investigate the key parameters in relation to the sensor sensitivity and resolution. The results showed that for high sensitivity and resolution, the frequency and magnitude of the ac driving current through the sensing element each has an optimum value, the resonance frequency of the signal pickup LC circuit should be equal to or twice as the driving frequency on the sensing element, and the anisotropy of the magnetic coating layer of the sensing wire element should be longitudinal.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.3
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• pp.306-312
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• 2019

This paper investigates to design a controller for maritime autonomous surface ship (MASS) by means of adaptive super-twisting algorithm (ASTA). A input-out feedback linearization method is considered for multi-input multi-output (MIMO) system. Sliding Mode Controller (SMC) is suitable for MASS subject to ocean environments due to its robustness against parameter uncertainties and disturbances. However, conventional SMC has inherent disadvantages so-called, chattering phenomenon, which resulted from the high frequency of switching terms. Chattering may cause harmful failure of actuators such as propeller and rudder of ships. The main contribution of this work is to address an appropriate controller for MASS, simultaneously controls surge and yaw motion in severe step inputs. Proposed control mechanism well provides convergence bewildered by external disturbances in the middle of steady-state responses as well as chattering attenuation. Also, the adaptive algorithm is contributed to reducing non-overestimated value of control gains. Control inputs of surge and yaw motion are displayed by smoother curves without excessive control activities of actuators. Finally, no overshoot can be seen in transient responses.

• Journal of Power Electronics
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• v.19 no.3
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• pp.665-675
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• 2019

Renewable energy based on photovoltaic systems is beginning to play an important role to supply power to remote areas all over the world. Owing to the lower output voltage of photovoltaic arrays, high gain DC-DC converters with a high efficiency are required in practice. This paper presents a novel interleaved DC-DC boost converter with a high voltage gain, where the input terminal is interlaced in parallel and the output terminal is staggered in series (IPOSB). The IPOSB configuration can reduce input current ripples because two inductors are interlaced in parallel. The double output capacitors are charged in staggered parallel and discharged in series for the load. Therefore, IPOSB can attain a high step-up conversion and a lower output voltage ripple. In addtion, the output voltage can be automatically divided by two capacitors, without the need for extra sharing control methods. At the same time, the voltage stress of the power devices is lowered. The inrush current problem of capacitors is restrained by the inductor when compared with high gain converters with a switching-capacitor structure. The working principle and steady-state characteristics of the converter are analyzed in detail. The correctness of the theoretical analysis is verified by experimental results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.114-130
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• 2021

With the drastic growth of Information and Communication Technology (ICT) industry, global energy consumption is exponentially increased by mobile communications. The huge energy consumption and increased environmental awareness have triggered great interests on the research of dynamic distribution of cell user and traffic, and then designing the energy efficient cellular network. In this paper, we explore the temporal and spatial characteristics of human mobility and traffic distribution using real data set. The analysis results of cell traffic illustrate the tidal effect in temporal and spatial dimensions and obvious periodic characteristics which can be used to design Base Station (BS) dynamic with sleeping or shut-down strategy. At the same time, we designed a new Cell Zooming and BS cooperation mode. Through simulation experiments, we found that running in this mode can save about 35% of energy consumption and guarantee the required quality of service.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.12
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• pp.4725-4747
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• 2020

Software defined networking (SDN) is considered to be one of the most promising paradigms in the future. To solve the scalability and performance problem that a single and centralized controller suffers from, the distributed multi-controller architecture is adopted, thus forms multi-domain SDN. In a multi-domain SDN network, it is of great importance to ensure a reliable control plane. In this paper, we focus on the reliability problem of multi-domain SDN against controller failure from perspectives of backup controller deployment and controller replication. We firstly propose a placement algorithm for backup controllers, which considers both the reliability and the cost factors. Then a controller replication mechanism based on shared data storage is proposed to solve the inconsistency between the active and standby controllers. We also propose a shared data storage layout method that considers both reliability and performance. Besides, a fault recovery and repair process is designed based on the controller backup and shared data storage mechanism. Simulations show that our approach can recover and repair controller failure. Evaluation results also show that the proposed backup controller placement approach is more effective than other methods.

• Journal of the Korean institute of surface engineering
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• v.55 no.1
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• pp.1-8
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• 2022

Titanium dioxide (TiO₂) is one of the most intensively investigated materials in materials science. Mostly, TiO₂ has been used in the form of nanoparticles, but recently new highly ordered TiO₂ nanotubes (U-tube) has been introduced and applied to various applications due to their one-dimensional charge path way. In the present paper, we described the formation process and physical properties of U-tube then, gave examples of applications in sequence. Firstly, in photocatalysis, U-tube was used with Au/Pt co-catalysts and showed enhanced photogenerated H₂ efficiency compared to bare TiO₂. Secondly, photoelectrochemical performance of U-tube was evaluated with different heat-treatment temperatures. As a further application, two different types of electrical cell (Ti-TiO₂-Pt and Ti-TiO₂-Pt_NP) was configurated to observe memristive behavior of U-tube. Both cells behaved as switching electrodes and follow a memristive movement in the high and low resistance state extremely well with high reproducibility.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.124-132
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• 2023

In this paper, we present a simple classification model based on statistical features and demonstrate the successful implementation of a brain-computer interface (BCI) based light on/off control system. This research shows study and development of light on/off control system based on BCI technology, which allows the users to control switching a lamp using electroencephalogram (EEG) signals. The logistic regression algorithm is used for classification of the EEG signal to convert it into light on, light off control commands. Training data were collected using 14-channel BCI system which records the brain signals of participants watching a screen with flickering lights and saves the data into .csv file for future analysis. After extracting a number of features from the data and performing classification using logistic regression, we created commands to switch on a physical lamp and tested it in a real environment. Logistic regression allowed us to quite accurately classify the EEG signals based on the user's mental state and we were able to classify the EEG signals with 82.5% accuracy, producing reliable commands for turning on and off the light.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.6
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• pp.1674-1688
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• 2023

The remarkable advancement of quantum steganography offers enhanced security for quantum communications. However, there is a significant concern regarding the potential misuse of this technology. Moreover, the current research on identifying malicious quantum steganography is insufficient. To address this gap in steganalysis research, this paper proposes a specialized quantum steganalysis algorithm. This algorithm utilizes quantum machine learning techniques to detect steganography in general quantum secure communication schemes that are based on pure states. The algorithm presented in this paper consists of two main steps: data preprocessing and automatic discrimination. The data preprocessing step involves extracting and amplifying abnormal signals, followed by the automatic detection of suspicious quantum carriers through training on steganographic and non-steganographic data. The numerical results demonstrate that a larger disparity between the probability distributions of steganographic and non-steganographic data leads to a higher steganographic detection indicator, making the presence of steganography easier to detect. By selecting an appropriate threshold value, the steganography detection rate can exceed 90%.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.85-85
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• 2022

The world's most extensive and active deltas, Louisiana's wetlands, are deteriorating rapidly due to multiple stressors such as the discharge of the Mississippi River, sea-level rise, and coastal retreat, the substantial but spatially and temporally variable impacts. However, the ecological and anthropogenic histories, the mode of environmental changes on a multi-millennial timescale have not been thoroughly documented. This study, a palynology-based multiproxy analysis, investigates hydrological, geological, geochemical, and anthropogenic impacts on southern Louisiana wetlands and a variety of external forcing agents influencing ecological succession. Sediment cores extracted from a small pond on a mangrove-dominate island near Port Fourchon, Louisiana, USA yielded a 4,000-year record. The site has been transformed from freshwater to saline water environments, to a mangrove dominant island over the late Holocene. The multivariate principal component analysis identified the relative strength of external drivers responsible for each ecological shift. The Mississippi River delta cycle (lobe switching) was the dominant driver of ecosystem changes during the late Holocene, while relative sea-level rise, tropical cyclones, climate, and anthropogenic effects have been the main drivers late in the site's history.