• Environmental Mutagens and Carcinogens
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• v.22 no.3
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• pp.175-182
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• 2002

Endocrine disruptors (EDs) are the chemicals that affect endocrine systems through activation or inhibition of steroid hormone response. It is necessary to have a good system to evaluate rapidly and accurately endocrine-disrupting activities of suspected chemicals and their degradation products. The key targets of EDs are nuclear hormone receptors, which bind to steroid hormones and regulate their gene transcription. We constructed a co-expression system of Gal4p DNA binding domain (DBD)- ligand binding domain of human estrogen receptor $\alpha$ or $\beta$, and Gal4p transactivation domain (TAD)-co-activator AIB-1, SRC-1 or TIF-2 in Saccharomyces cerevisiae with a chromosome-integrated lacZ reporter gene under the control of CYC1 promoter and Gal4p binding site (GAL4 upstream activating sequence, GAL4$_{UAS}$). Expression of this reporter gene was dependent on the presence of estrogen or EDs in the culture medium. We found that the two-hybrid system with combination of the hER$\beta$ LBD and co-activator SRC-1 was most effective in the xenoestrogen-dependent induction of reporter activity. The extent of transcriptional activation by those chemicals correlated with their estrogenic activities measured by other assay systems, indicating that this assay system is efficient and reliable for measuring estrogenic activity. The data in this research demonstrated that the yeast detection system using steroid hormone receptor and co-activator is a useful tool for identifying chemicals that interact with steroid receptors.s.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.38 no.8
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• pp.701-707
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• 2014

The ecofriendly yellow ocher is used in the manufacturing of cosmetics, construction, and food packaging. The polyethylene terephthalate (PET) used for manufacturing food containers has a microporous structure that causes aeration. Hydrophilic yellow ocher may be applied to hydrophobic PET by surface modification to overcome this issue. The aim of this study is to fabricate a yellow ocher polystyrene hybrid structure in the form of nanoparticles using an optimizing molar ratio of styrene, divinylbenzene, and potassium peroxodisulfate for use in emulsion polymerization. The polymerization was conducted in a yellow ocher suspension that was prepared by dispersing mechanically ground yellow ocher in DI water. The prepared hybrid structure was measured using scanning electron microscopy, energy dispersive X-ray spectroscopy, and X-ray diffraction. The measurement revealed the spherical morphology and Si component that resulted from the yellow ocher in the polystyrene particles. We expect that this hybrid structure would be used as platform material to minimize aeration in PET.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.1
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• pp.1-9
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• 2017

With the Development of Wireless Network Technology and Wireless Link Technology, Wireless Mesh Network (WMN) is Attracting Attention as a Key Technology to Construct the Wireless Transit Network. The WMN has been Studied for a Long Time in Various Fields, however there are still many Problems that have not been solved yet. One of them is the Routing Problem to find an Optimal path in a Multi-hop Network Composed of Wireless Links. In the Hybrid-WMN, which is one of the Three Types of WMN, Optimal Path Selection Requires Research on Path Search Protocols that Effectively use the Infrastructure Mesh as a Transit Network, Together with Research for a Routing Metric with Excellent Performance. Therefore, this Paper Proposes a Dual Mode-AODV(Ad hoc On-demand Distance Vector) for Hybrid-WMN. Simulation result shows that the Path Selection Delay was Reduced by 52% than AODV when the Proposed Dual Mode-AODV was applied.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.5
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• pp.128-134
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• 2018

In this paper, two ports feeding a microstrip patch antenna using a quadrature hybrid circuit was proposed to enhance the bandwidth for the global positioning system(GPS). The square patch was designed, and the probe feeding was applied. The quadrature hybrid chip circuit for two-port feeding was designed, and output ports that have a 90-degree phase difference feed to the patch antenna. The designed patch and quadrature hybrid circuit were implemented on an FR4 board, and were combined. The measurement of the bandwidth within a voltage standing wave ratio(VSWR) of 2:1 and axial ratio(AR) in 3dB were wide band as 29% BW (1,230~1,700 MHz) and 15.87% BW (1,400~1,650 MHz), respectively. Antenna gain were measured 2.75dBi at the center frequency.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.4
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• pp.448-453
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• 2012

There are many researches to develop robots that improve its mobility to adapt in various uneven environments. In the paper, a hybrid wheeled and legged mobile robot is designed and a obstacle avoidance algorithm is proposed based on low power walking using LRF(Laser Range Finder). In order to stabilize the robot's motion and reduce energy consumption, we implement a low-power walking algorithm through comparison of the current value of each motors and correction of posture balance. A low-power obstacle avoidance algorithm is proposed by using LRF sensor. We improve walking stability by distributing power consumption and reduce energy consumption by selecting a shortest navigation path of the robot. The proposed methods are verified through walking and navigation experiments with the developed hybrid robot.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.4 s.316
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• pp.117-122
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• 2007

For multiple antenna systems, we consider the hybrid iterative detection of the maximum a posteriori probability(MAP) detection and the linear detection such as the minimum-mean-square-error(MMSE) filtering with soft cancelation. We devise methods to obtain both the lower complexity of the linear detection and the superior performance of the MAP detection. Using the a prior probability of the coded bit which is extrinsic of the outer decoder, we compute the threshold of grouping and determine the detection scheme symbol by symbol. Through the simulation results, it is shown that the proposed receiver obtains the superior performance to the MMSE detector and the lower complexity than the MAP detector.

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.6
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• pp.296-305
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• 2005

TCP/IP, the most popular communication protocol, is processed on a host CPU in traditional computer systems and this imposes enormous loads on the host CPU. Recently TCP/IP Offload Engine (TOE) technology, which processes TCP/IP on a network adapter instead of the host CPU, becomes an important way to solve the problem. In this paper we analysed the structure of a TCP/IP protocol stack in the Linux operating system and important factors, which cause a lot of loads on the host CPU, by measuring the time spent on processing each function in the protocol stack. Based on these analyses, we propose a Hybrid TOE architecture, in which functions imposing much loads on the host CPU are implemented using hardware and other functions are implemented using software.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.8
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• pp.662-668
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• 2013

Mobile communication systems have been adopting link adaptive transmission schemes such as adaptive modulation and coding (AMC) and hybrid-ARQ (HARQ). Incremental redundancy (IR) HARQ scheme is known to be highly efficient in terms of throughput and power consumption and can be a good solution for mobile communication systems. In this paper, we propose an IR-HARQ scheme based on dual-diagonal parity-type block LDPC codes in which we define a transmission priority of coded bits and propose the sub-packet construction rule. We present the throughput performance of IR-HARQ with various modulation and coding and multi-antenna modes. Consequently, the proposed scheme provides the improvement of system throughput by elaborate link adaptation with CQI information.

• Journal of Ocean Engineering and Technology
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• v.18 no.4 s.59
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• pp.33-39
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• 2004

This paper presents a hybrid underwater navigation system for unmanned underwater vehicles, using an additional range sonar, where the navigation system is based on inertial and Doppler velocity sensors. Conventional underwater navigation systems are generally based on an inertial measurement unit (IMU) and a Doppler velocity log (DVL), accompanying a magnetic compass and a depth sensor. Although the conventional navigation systems update the bias errors of inertial sensors and the scale effects of DVL, the estimated position slowly drifts as time passes. This paper proposes a measurement model that uses the range sonar to improve the performance of the IMU-DVL navigation system, for extended operation of underwater vehicles. The proposed navigation model includes the bias errors of IMU, the scale effects of VL, and the bias error of the range sonar. An extended Kalman filter was adopted to propagate the error covariance, to update the measurement errors, and to correct the state equation, when the external measurements are available. To illustrate the effectiveness of the hybrid navigation system, simulations were conducted with the 6-d.o.f. equations of motion of an AUV in lawn-mowing survey mode.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.277-282
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• 2006

It is well known that Kalman filtering is an optimal real-time data fusion method for GPS/INS integration. However, it has some limitations in terms of stability, adaptability and observability. A Kalman filter can perform optimally only when its dynamic model is correctly defined and the noise statistics for the measurement and process are completely known. It is found that estimated Kalman filter states could be influenced by several factors, including vehicle dynamic variations, filter tuning results, and environment changes, etc., which are difficult to model. Neural networks can map input-output relationships without apriori knowledge about them; hence a proper designed neural network is capable of learning and extracting these complex relationships with enough training. This paper presents a GPS/INS integrated system that combines Kalman filtering and neural network algorithms to improve navigation solutions during GPS outages. An Extended Kalman filter estimates INS measurement errors, plus position, velocity and attitude errors etc. Kalman filter states, and gives precise navigation solutions while GPS signals are available. At the same time, a multi-layer neural network is trained to map the vehicle dynamics with corresponding Kalman filter states, at the same rate of measurement update. After the output of the neural network meets a similarity threshold, it can be used to correct INS measurements when no GPS measurements are available. Selecting suitable inputs and outputs of the neural network is critical for this hybrid method. Detailed analysis unveils that some Kalman filter states are highly correlated with vehicle dynamic variations. The filter states that heavily impact system navigation solutions are selected as the neural network outputs. The principle of this hybrid method and the neural network design are presented. Field test data are processed to evaluate the performance of the proposed method.