• Proceedings of the Korean Magnestics Society Conference
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• 2000.09a
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• pp.352-362
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• 2000

In this study, effects of novel VMn underlayer on magnetic properties of CoCrPt/VMn longitudinal medium was studied and compared with those of CoCrPt/Cr medium. It was found that the VMn film had (200) preferred orientation and the lattice constant was about 0.2967 nm, which is slightly larger than that of the Cr, 0.2888 nm. The grain size of VMn film was 9.3 nm at 30 nm thickness, and this is about 38 % smaller than that of a similarly deposited Cr film. The CoCrPt/VMn films showed higher coercivity in comparison with the CoCrPt/Cr films. The coercivity increase seems to be attributed to the increased Co (11.0) texture, improved lattice matching between Co (11.0) and VMn (200), and lower stacking fault density. Mn must have diffused into the CoCrPt magnetic layer more uniformly rather than preferentially along grain boundaries this reduced Ms at higher substrate temperature

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2009.06a
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• pp.11-12
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• 2009

In this paper, we propose a high voltage driver IC(HVIC) for LCD and PDP TV power supply. The proposed circuit is included novel a shoot-through protection and a pulse generation circuit for the high voltage driver IC. The proposed circuit has lower variation of dead time and pulse-width about a variation of a process and a supply voltage than a conventional circuit. Especially, the proposed circuit has more excellent pulse-width matching of set and reset signals than the conventional circuit. Also the proposed pulse generation circuit prevent from fault operations using a logic gate. Dead time and pulse-width of the proposed circuit are typical 250 ns, and its variation is maximum 170 ns(68 %) about a variation of a process and a supply voltage. The proposed circuit is designed using $1\;{\mu}m$ 650 V BCD process parameter, and a simulation is carried out using Spectre.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.22 no.10
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• pp.801-807
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• 2009

In this paper, we propose a novel shoot-through protection circuit and pulse generator for half-bridge driver IC. We designed a robust half-bridge driver IC over a variation of processes and power supplies. The proposed circuit is composed a delay circuit using a beta-multiplier reference. The proposed circuit has a lower variation rate of dead time and pulse-width over variation of processes and supply voltages than the conventional circuit. Especially, the proposed circuit has more excellent pulse-width matching of set and reset signals than the conventional circuit. Also, the proposed pulse generator is prevented from fault operations using a logic gate. Dead time and pulse-width of the proposed circuit are typical 250 ns, respectively. The variation ratio is 68%(170 ns) of maximum over variation of processes and supply voltages. The proposed circuit is designed using $1\;{\mu}m$ 650 V BCD (Bipolar, CMOS, DMOS) process parameter, and the simulations are carried out using Spectre simulator of Cadence corporation.

• Journal of Korean Society of Environmental Engineers
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• v.29 no.8
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• pp.944-949
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• 2007

The profiles of on-line sensors such as DO, ORP and pH can provide useful information about pollutant removal reaction in sequencing batch reactor. For detection of denitrification completion, the nitrate hee point from ORP profile has been considered as a main indicator of denitrification completion. However, many researchers pointed out that the nitrate knee usually disappeared been the progress of denitrification is so fast and it makes the fault at detection of denitrification completion. In this paper, dynamic time warping(DTW) method and discriminant analysis were used to detect and isolate the profiles of two cases, denitrification completed and uncompleted. As the results, proposed methods can detect state of denitrification successfully.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.7
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• pp.3747-3765
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• 2017

Existing authentication mechanisms in cellular mobile communication networks are realized in the upper layer by employing cryptographic techniques. Authentication data are broadcasted over the air in plaintext, enabling attackers to completely eavesdrop on the authentication and get some information about the shared secret key between legitimate nodes. Therefore, reusing the same secret key to authenticate several times results in the secret key's information leakage and high attacking rate. In this paper, we consider the most representative authentication mechanism, Authentication and Key Agreement (AKA), in cellular communication networks and propose an enhanced AKA scheme based on Physical Layer Authentication (AKA-PLA). Authentication responses generated by AKA are no longer transmitted in plaintext but masked by wireless channel characteristics, which are not available to adversaries, to generate physical layer authentication responses by a fault-tolerant hash method. The authenticator sets the threshold according to the authentication requirement and channel condition, further verifies the identity of the requester based on the matching result of the physical layer authentication responses. The performance analyses show that the proposed scheme can achieve lower false alarm rate and missing rate, which are a pair of contradictions, than traditional AKA. Besides, it is well compatible with AKA.

• Journal of the Korean Society of Industry Convergence
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• v.8 no.1
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• pp.11-17
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• 2005

This study was performed to analysis the operation process when fabric pattern design was done by the use of CAD system compared with the manual work in order to determine the operation efficiency with the application of fabric design CAD system. The results of the study were as follows: 1. since 160,000 colors were supported by CAD system, color proposed by consumer was able to match exactly according to the its design. However, exact color matching was not possible by manual work. 2. Woven state of back of pattern design could be identified simultaneously with face of it for CAD system, while face and back of the fabrics should be designed separatedly in case of manual work. 3. Since the combination of warp and filling yarn was compatible with the fabric density in one repeat unit in CAD system, exact size of pattern design to be woven was able to expressed. 4. Only simple graphical expression by manual work was seen, while with the CAD system, texture and shade effect as well as graphical expression could be expressed and so fault could be reduced in advance with the simulation of actual feeling of fabrics in the screen. In conclusion, when CAD system will be introduced to the textile industry, operation time of designing pattern can be reduced. Since the operation is easy and simple, a beginner can operate CAD system easily. Thus, production and wage costs can be saved and this can be related directly with the improvement of productivity which is the main purpose of introducing CAD system.

• International journal of advanced smart convergence
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• v.4 no.2
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• pp.109-119
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• 2015

The interaction between wireless sensors such as Internet of Things (IoT) and Cloud is a new paradigm of communication virtualization to overcome resource and efficiency restriction. Cloud computing provides unlimited platform, resources, services and also covers almost every area of computing. On the other hand, Wireless Sensor Networks (WSN) has gained attention for their potential supports and attractive solutions such as IoT, environment monitoring, healthcare, military, critical infrastructure monitoring, home and industrial automation, transportation, business, etc. Besides, our virtual groups and social networks are in main role of information sharing. However, this sensor network lacks resource, storage capacity and computational power along with extensibility, fault-tolerance, reliability and openness. These data are not available to community groups or cloud environment for general purpose research or utilization yet. If we reduce the gap between real and virtual world by adding this WSN driven data to cloud environment and virtual communities, then it can gain a remarkable attention from all over, along with giving us the benefit in various sectors. We have proposed a Pub/Sub-based sensor virtualization framework Cloud environment. This integration provides resource, service, and storage with sensor driven data to the community. We have virtualized physical sensors as virtual sensors on cloud computing, while this middleware and virtual sensors are provisioned automatically to end users whenever they required. Our architecture provides service to end users without being concerned about its implementation details. Furthermore, we have proposed an efficient content-based event matching algorithm to analyze subscriptions and to publish proper contents in a cost-effective manner. We have evaluated our algorithm which shows better performance while comparing to that of previously proposed algorithms.

• Geophysics and Geophysical Exploration
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• v.25 no.1
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• pp.1-13
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• 2022

For surveying shallow gas reservoirs in the Pohang basin, we proposed a seismic exploration method applicable to the transition zone in which land and marine areas are connected. We designed the seismic acquisition geometry considering both environments. We installed land nodal receivers on the ground and employed vibroseis and airgun sources in both land and marine areas. For seismic exploration in the transition zone, specific acquisition and processing techniques are required to ensure precise matching of reflectors at the boundary between the onshore and offshore regions. To enhance the continuity of reflection events on the seismic section, we performed amplitude and phase corrections with respect to the source types and applied a static correction. Following these processing steps, we obtained a seismic section showing connected reflectors around the boundary in the transition zone. We anticipate that our proposed seismic exploration method can also be used for fault detection in the transition zone.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.7
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• pp.299-306
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• 2022

In recent, sensors embedded in robots, equipment, and circuits have become common, and research for diagnosing device failures by learning measured sensor data is being actively conducted. This failure diagnosis study is divided into a classification model for predicting failure situations or types and a regression model for numerically predicting failure conditions. In the case of a classification model, it simply checks the presence or absence of a failure or defect (Class), whereas a regression model has a higher learning difficulty because it has to predict one value among countless numbers. So, the reason that regression modeling is more difficult is that there are many irregular situations in which it is difficult to determine one output from a similar input when predicting by matching input and output. Therefore, in this paper, we focus on input and output data with periodicity, analyze the input/output relationship, and secure regularity between input and output data by performing sliding window-based input data patterning. In order to apply the proposed method, in this study, current and temperature data with periodicity were collected from MMC(Modular Multilevel Converter) circuit system and learning was carried out using ANN. As a result of the experiment, it was confirmed that when a window of 2% or more of one cycle was applied, performance of 97% or more of fit could be secured.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.47-73
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• 2020

KTX rolling stocks are a system consisting of several machines, electrical devices, and components. The maintenance of the rolling stocks requires considerable expertise and experience of maintenance workers. In the event of a rolling stock failure, the knowledge and experience of the maintainer will result in a difference in the quality of the time and work to solve the problem. So, the resulting availability of the vehicle will vary. Although problem solving is generally based on fault manuals, experienced and skilled professionals can quickly diagnose and take actions by applying personal know-how. Since this knowledge exists in a tacit form, it is difficult to pass it on completely to a successor, and there have been studies that have developed a case-based rolling stock expert system to turn it into a data-driven one. Nonetheless, research on the most commonly used KTX rolling stock on the main-line or the development of a system that extracts text meanings and searches for similar cases is still lacking. Therefore, this study proposes an intelligence supporting system that provides an action guide for emerging failures by using the know-how of these rolling stocks maintenance experts as an example of problem solving. For this purpose, the case base was constructed by collecting the rolling stocks failure data generated from 2015 to 2017, and the integrated dictionary was constructed separately through the case base to include the essential terminology and failure codes in consideration of the specialty of the railway rolling stock sector. Based on a deployed case base, a new failure was retrieved from past cases and the top three most similar failure cases were extracted to propose the actual actions of these cases as a diagnostic guide. In this study, various dimensionality reduction measures were applied to calculate similarity by taking into account the meaningful relationship of failure details in order to compensate for the limitations of the method of searching cases by keyword matching in rolling stock failure expert system studies using case-based reasoning in the precedent case-based expert system studies, and their usefulness was verified through experiments. Among the various dimensionality reduction techniques, similar cases were retrieved by applying three algorithms: Non-negative Matrix Factorization(NMF), Latent Semantic Analysis(LSA), and Doc2Vec to extract the characteristics of the failure and measure the cosine distance between the vectors. The precision, recall, and F-measure methods were used to assess the performance of the proposed actions. To compare the performance of dimensionality reduction techniques, the analysis of variance confirmed that the performance differences of the five algorithms were statistically significant, with a comparison between the algorithm that randomly extracts failure cases with identical failure codes and the algorithm that applies cosine similarity directly based on words. In addition, optimal techniques were derived for practical application by verifying differences in performance depending on the number of dimensions for dimensionality reduction. The analysis showed that the performance of the cosine similarity was higher than that of the dimension using Non-negative Matrix Factorization(NMF) and Latent Semantic Analysis(LSA) and the performance of algorithm using Doc2Vec was the highest. Furthermore, in terms of dimensionality reduction techniques, the larger the number of dimensions at the appropriate level, the better the performance was found. Through this study, we confirmed the usefulness of effective methods of extracting characteristics of data and converting unstructured data when applying case-based reasoning based on which most of the attributes are texted in the special field of KTX rolling stock. Text mining is a trend where studies are being conducted for use in many areas, but studies using such text data are still lacking in an environment where there are a number of specialized terms and limited access to data, such as the one we want to use in this study. In this regard, it is significant that the study first presented an intelligent diagnostic system that suggested action by searching for a case by applying text mining techniques to extract the characteristics of the failure to complement keyword-based case searches. It is expected that this will provide implications as basic study for developing diagnostic systems that can be used immediately on the site.