• Applied Chemistry for Engineering
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• v.22 no.5
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• pp.551-554
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• 2011

One of the key issues in the research of organic field-effect transistors (OFETs) is the low-voltage operation. To address this issue, we synthesized poly(styrene-r-benzocyclobutene-r-methyl methacrylate) (P(S-r-BCB-r-MMA)) as a thermally cross-linkable gate dielectrics. The P(S-r-BCB-r-MMA) showed high quality dielectric properties due to the negligible volume change during the cross-linking. The pentacene FETs based on the 34 nm-thick P(S-r-BCB-r-MMA) gate dielectrics operate below 5 V. The P(S-r-BCB-r-MMA) gate dielectrics yielded high device performance, i.e. a field-effect mobility of $0.25cm^2/Vs$, a threshold voltage of -2 V, an sub-threshold slope of 400 mV/decade, and an on/off current ratio of ${\sim}10^5$. The thermally cross-linkable P(S-r-BCB-r-MMA) will provide an attractive candidate for solution-processable gate dielectrics for low-voltage OFETs.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.5
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• pp.93-101
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• 2008

Side channel attacks are well known as one of the most powerful physical attacks against low-power cryptographic devices and do not take into account of the target's theoretical security. As an important succeeding factor in side channel attacks (specifically in DPAs), exact time-axis alignment methods are used to overcome misalignments caused by trigger jittering, noise and even some countermeasures intentionally applied to defend against side channel attacks such as random clock generation. However, the currently existing alignment methods consider only on the position of signals on time-axis, which is ineffective for certain countermeasures based on time-axis misalignments. This paper proposes a new signal alignment method based on interpolation and decimation techniques. Our proposal can align the size as well as the signals' position on time-axis. The validity of our proposed method is then evaluated experimentally with a smart card chip, and the results demonstrated that the proposed method is more efficient than the existing alignment methods.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.19 no.5
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• pp.131-142
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• 2009

While users of information security products require high-quality products that are secure and have high performance, there are neither examples for evaluating the quality of information security products nor studies on the quality model and metrics for the quality evaluation. In this paper, information security products are categorized into three different types and the security and performance of various information security products are analyzed. Through this process and after consideration of information security products' security and performance, a new quality model that possesses 7 characteristics and 24 sub-characteristics has been defined. In addition, metrics consisting of 62 common and 45 extended metrics that can be used to evaluate the quality of information security products are introduced, and a proposition for a method of generating the quality evaluation metrics for specific information security products is included. The method of generating metrics proposed in this paper can be extended in order to be applied to a variety of information security products, and by generating and verifying the quality evaluation metrics for firewall, intrusion detection systems and fingerprint systems it is shown that it applicable on a variety of information security products.

• The Journal of Bigdata
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• v.5 no.2
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• pp.77-84
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• 2020

In this study, we conducted a study on the win-loss predicton analysis of korean professional baseball by artificial intelligence models. Based on the model, we predicted the winner as well as each team's final rank in the league. Additionally, we developed a website for viewers' understanding. In each game's first, third, and fifth inning, we analyze to select the best model that performs the highest accuracy and minimizes errors. Based on the result, we generate the rankings. We used the predicted data started from May 5, the season's opening day, to August 30, 2020 to generate the rankings. In the games which Kia Tigers did not play, however, we used actual games' results in the data. KNN and AdaBoost selected the most optimized machine learning model. As a result, we observe a decreasing trend of the predicted results' ranking error as the season progresses. The deep learning model recorded 89% of the model accuracy. It provides the same result of decreasing ranking error trends of the predicted results that we observe in the machine learning model. We estimate that this study's result applies to future KBO predictions as well as other fields. We expect broadcasting enhancements by posting the predicted winning percentage per inning which is generated by AI algorism. We expect this will bring new interest to the KBO fans. Furthermore, the prediction generated at each inning would provide insights to teams so that they can analyze data and come up with successful strategies.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.3
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• pp.123-128
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• 2021

For accurate speed and current control in industrial applications, SRM (Switched Reluctance Motor) is very important to synchronize the stator phase excitation and rotor position in the drive due to its nature. In general, position sensors such as encoder and resolver are used to generate rotational force by exciting the stator winding according to the rotor position and to control the motor by using speed and position information. However, for these sensors, 1) the cost of the sensors is quite large in terms of price, so the proportion of the motor system to the total system cost is high. 2) In terms of mechanical, position sensors such as encoders and resolvers are attached to the stator to increase the size and weight. In conclusion, in order to drive the SRM, control based on the rotor position information should be basically performed, and it is important to design the SRM driving system according to the environment in consideration of the application field. Therefore, in this paper, we intend to study the driving and control characteristics of SRM through variable switching duty control by designing a low-cost analog driving device, deviating from the general control system using the conventional encoder and resolver.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.801-807
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• 2021

In various industrial fields and infrastructure based on electronic components, such as communication equipment, transportation, computer networks, and military equipment, the need for electromagnetic pulse shielding has increased. Two methods for applying electromagnetic pulse shielding are effective. The first is construction using shielding materials, such as shielding concrete, shielding doors, and shielding windows. The other is coating shielding paints on non-shielding structures. Electromagnetic pulse shielding paints are made using conductive materials, such as carbon nanotubes, graphite, carbon black, and carbon fiber. In this paint, electromagnetic pulse shielding performance is added to the commonly used water-based paint. In this study, the shielding effectiveness and bonding performance of paints using conductive graphite and carbon black as shielding materials were evaluated to develop electromagnetic pulse shielding inorganic paints. The shielding effectiveness and bonding performance were evaluated by applying six mixtures composed of different kinds and amounts of shielding material. The mixture of conductive graphite and carbon black at a weight ratio of 1:0.2 was the most effective in shielding as 33.6 dB. Furthermore, the mixture produced using conductive graphite only showed the highest bonding performance of 1.06 MPa.

• Geophysics and Geophysical Exploration
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• v.24 no.3
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• pp.78-88
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• 2021

Owing to the abnormal weather conditions due to global warming, carbon capture and storage (CCS) technology has attracted global attention as a countermeasure to reduce CO₂ emissions. In the Pohang CCS demonstration project in South Korea, 100 tons of CO₂ were successfully injected into the subsurface CO₂ storage in early 2017. However, after the 2017 Pohang earthquake, the Pohang CCS demonstration project was suspended due to an increase in social concerns about the safety of the CCS project. In this study, to reconfirm the structural suitability of the CO₂ storage site in the Pohang Basin, we employed seismic imaging based on reverse-time migration (RTM) to analyze small-scale ocean-bottom seismic data, which have not been utilized in previous studies. Compared with seismic images using marine streamer data, the continuity of subsurface layers in the RTM image using the ocean-bottom seismic data is improved. Based on the obtained subsurface image, we discuss the structural suitability of the Pohang CO₂ storage site.

• Clean Technology
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• v.27 no.2
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• pp.132-138
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• 2021

Research is being conducted on graphene to provide graphene having both excellent physical as well as electrical properties in addition to unique physical properties. In this study, Hummer's method, which is a representative method for chemical exfoliation, was applied in order to investigate the possibility of the mass production of high-quality graphene oxide. Three types of graphite (graphite, crystalline graphite, and expanded graphite) were used in the preparation of graphene oxide with variations in the amount of potassium permanganate added, reaction temperature, and reaction time. Then a Fourier transform infrared spectroscopy (FT-IR), a Raman spectrometer, and a transmission electron microscope (TEM) were used to measure the quality of the prepared graphene oxide. Of the three types of graphite used in this experiment, crystalline graphite showed the highest quality. The prepared graphene oxide was then purified with an organic solvent, and an analysis conducted using energy dispersive X-ray spectroscopy (EDS). From the results of the residual values, we were able to confirm that both acid wastewater and wastewater were best purified using cyclohexane. The method for manufacturing graphene oxide as well as the method of purification using organic solvents that are presented in this study are expected to have less of an environmental impact, making them environmentally friendly. This makes them suitable for use in various industrial fields such as the film industry and for heat dissipation and as coating agents.

• Journal of the Korea Society for Simulation
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• v.31 no.1
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• pp.29-41
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• 2022

As one of the alternatives to solve the problem of unstable food supply and demand imbalance caused by abnormal climate change, the need for plant factories is increasing. Airflow in plant factory is recognized as one of important factor of plant which influence transpiration and heat transfer. On the other hand, Digital Twin (DT) is getting attention as a means of providing various services that are impossible only with the real system by replicating the real system in the virtual world. This study aimed to develop a digital twin model for airflow prediction that can predict airflow in various situations by applying the concept of digital twin to a plant factory in operation. To this end, first, the mathematical formalism of the digital twin model for airflow analysis in plant factories is presented, and based on this, the information necessary for airflow prediction modeling of a plant factory in operation is specified. Then, the shape of the plant factory is implemented in CAD and the DT model is developed by combining the computational fluid dynamics (CFD) components for airflow behavior analysis. Finally, the DT model for high-accuracy airflow prediction is completed through the validation of the model and the machine learning-based calibration process by comparing the simulation analysis result of the DT model with the actual airflow value collected from the plant factory.

• Journal of Broadcast Engineering
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• v.27 no.2
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• pp.185-197
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• 2022

Recently, deep learning networks with high performance for object recognition are emerging. In the case of object recognition using deep learning, it is important to build a training data set to improve performance. To build a data set, we need to collect and label the images. This process requires a lot of time and manpower. For this reason, open data sets are used. However, there are objects that do not have large open data sets. One of them is data required for license plate detection and recognition. Therefore, in this paper, we propose an artificial license plate generator system that can create large data sets by minimizing images. In addition, the detection rate according to the artificial license plate arrangement structure was analyzed. As a result of the analysis, the best layout structure was FVC_III and B, and the most suitable network was D2Det. Although the artificial data set performance was 2-3% lower than that of the actual data set, the time to build the artificial data was about 11 times faster than the time to build the actual data set, proving that it is a time-efficient data set building system.