• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.3
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• pp.465-479
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• 2020

Regardless of the domestic and foreign governments/companies, SOC (Security Operation Center) has operated 24 hours a day for the entire year to ensure the security for their IT infrastructures. However, almost all SOCs have a critical limitation by nature, caused from heavily depending on the manual analysis of human agents with the text-based monitoring architecture. Even though, in order to overcome the drawback, technologies for a comprehensive visualization against complex cyber threats have been studying, most of them are inappropriate for the security monitoring in large-scale networks. In this paper, to solve the problem, we propose a novel visual approach for intuitive threats monitoring b detecting suspicious IP address, which is an ultimate challenge in cyber security monitoring. The approach particularly makes it possible to detect, trace and analysis of suspicious IPs statistically in real-time manner. As a result, the system implemented by the proposed method is suitably applied and utilized to the real-would environment. Moreover, the usability of the approach is verified by successful detecting and analyzing various attack IPs.

• Applied Microscopy
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• v.28 no.2
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• pp.139-158
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• 1998

The development of the superior cervical ganglion was studied by electron microscopic method in human fetuses ranging from 40 mm to 260 mm of crown-rump length (10 to 30 weeks of gestational age). At 40 mm fetus, the superior cervical ganglion was composed of clusters of undifferentiated cell, primitive neuroblast, primitive supporting cell, and unmyelinated fibers. At 70mm fetus, the neuroblasts and their processes were ensheated by the bodies or processes of satellite cells. The cytoplasm of the neuroblast contained rough endoplasmic reticulum, mitochondria, Golgi complex, Nissl bodies and dense-cored vesicles. As the neuroblasts grew and differentiated dense-cored vesicles moved away from perikaryal cytoplasm into developing processes. Synaptic contacts between the cholinergic axon and dendrites of postganglionic neuron and a few axosomatic synapses were first observed at 70 mm fetus. At 90 mm fetus the superior cervical ganglion consisted of neuroblasts, satellite cells, granule-containing cells, and unmyelinated nerve fibers. The ganglion cells increased somewhat in numbers and size by 150 mm fetus. Further differentiation resulted in the formation of young ganglion cells, whose cytoplasm was densely filled with cell organelles. During next prenatal stage up to 260 mm fetus, the cytoplasm of the ganglion cells contained except for large pigment granules, all intracytoplasmic structures which were also found in mature superior cervical ganglion. A great number of synaptic contact zones between the cholinergic preganglionic axon and the dendrites of the postganglionic neuron were observed and a few axosomatic synapses were also observed. Two morphological types of the granule-containing cells in the superior cervical ganglion were first identified at 90 mm fetus. Type I granule-containing cell occurred in solitary, whereas type II tended to appeared in clusters near the blood capillaries. Synaptic contacts were first found on the solitary granule-containing cell at 150 mm fetus. Synaptic contacts between the soma of type I granule-containing cells and preganglionic axon termials were observed. In addition, synaptic junctions between the processes of the granule- containing cells and dendrites of postganglionic neuron were also observed from 150 mm fetus onward. In conclusion, superior cervical ganglion cells and granule-containing cells arise from a common undifferentiated cell precursor of neural crest . The granule-containg cells exhibit a local modulatory feedback system in the superior cervical ganglion and nay serve as interneurons between the preganglionic and postganglionic cells.

• The KIPS Transactions:PartD
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• v.13D no.5 s.108
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• pp.641-650
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• 2006

XML has the characteristics of self-describing and uses DTD or XML schema in order to constraint its structure. Even though the XML schema is only at the stage of recommendation yet, it will be prevalently used because DTD is not itself XML and has the limitation on the expression power. The structure defined by the XML schema as well as the data of the XML documents can vary due to complex reasons. Those reasons are errors in the XML schema design, new requirements due to new applications, etc. Thus, we propose XML schema evolution operators that are extracted from the analysis of the XML schema updates. These schema evolution operators enable the XML schema updates that would have been impossible without supporting tools if there are a large number of XML documents complying the U schema. In addition, these operators includes the function of automatically finding the update place in the XML documents which are registered to the XSE system, and maintaining the XML documents valid to the XML schema rather than merely well-formed. This paper is the first attempt to update XML schemas of the XML documents and provides the comprehensive set of schema updating operations. Our work is necessary for the XML application development and maintenance in that it helps to update the structure of the XML documents as well as the data in the easy and precise manner.

• The KIPS Transactions:PartA
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• v.15A no.6
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• pp.309-316
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• 2008

The mission-critical engagement control computer for air defense has to maintain its operation without any fault for a long mission time. The mission performed by large-scale and complex embedded software is extremely critical in terms of dependability and safety of computer system, and it is very important that engagement control computer has high reliability. The engagement control computer was implemented using four processors. The distributed computer composed of four processors quarantees the dependability and safety, and ASR fault-tolerant technique applied to each processor guarantees the reliability. In this paper, the mechanism and performance of ASR fault-tolerant technique are analysed. And MTBF, reliability, availability, and cost-effectiveness for ASR, DMR and TMR techniques applied to the engagement control computer are analysed. The mission-critical engagement control computer using software-based ASR fault-tolerant technique provides high reliability and fast recovery time at a low cost. The mission reliability of the engagement control computer using ASR technique in 4 processors board is almost same the reliability of the computer using TMR technique in 6 processors board. ASR technique is most suitable to the mission-critical engagement control computer.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.412-419
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• 2019

Negative space in the discipline of art defines the space around and between the subject of an image. The use of negative space is an element of artistic composition, since it is occasionally used to artistic effect as the "real" subject of an image. In painting, it is a technique that negatively touches the background of an object to be expressed, so that it gives a feeling of unique texture and silhouette by touching unnecessary parts while leaving necessary parts. As in art, negative space in a design can also be useful to identify an image of infeasible design ranges with a straightforward view. Similarity between two disciplines leads to the introduction of the negative space concept for design space exploration. A rough design space exploration using statistics and visual analytics may support more efficient decision-making, and can provide meaningful insights into the direction of early-phase system design. For this, the approach guarantees dynamic interactions between visualized information and human cognitive systems. Visual analytics is useful to summarize complex and large-scale data. It is useful for identifying feasible design spaces, as well as for avoiding infeasible spaces or highly risky spaces. This paper investigates the possible use of the negative space concept by using an application example.

• Journal of the Korea Society for Simulation
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• v.30 no.1
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• pp.113-126
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• 2021

The future energy consumption pattern will show a very different pattern from the present due to the increase of distributed power sources such as renewable energy and the birth of the concept of prosumers, etc. Accordingly, it can be predicted that the direction of establishment of an appropriate production and supply plan considering the stability and consumption efficiency of the entire power grid will also be different from now. This paper proposes a simulation model that can test a new operational strategy when faced with a number of possible future environments. Through the proposed model, it is possible to simulate and analyze power consumed and supplied in a future Smart Grid environment, in which a large amount of new concepts including energy storage service (ESS) and distributed energy resources (DER) will be added. In particular, it is possible to model complex systems structurally by using DEVS formalism among the ABM (Agent-Based Model) methodologies that can model decision-making for each agent existing in the grid, and several factors can be easily added to the grid. The simulation model was verified using given dataset in the current situation, and scenario analysis was performed by simply adding an ESS, one of the main elements of the smart grid, to the model.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.101-125
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• 2022

Recently, with the development of computing technology and the improvement of the cloud environment, deep learning technology has developed, and attempts to apply deep learning to various fields are increasing. A typical example is anomaly detection, which is a technique for identifying values or patterns that deviate from normal data. Among the representative types of anomaly detection, it is very difficult to detect a contextual anomaly that requires understanding of the overall situation. In general, detection of anomalies in image data is performed using a pre-trained model trained on large data. However, since this pre-trained model was created by focusing on object classification of images, there is a limit to be applied to anomaly detection that needs to understand complex situations created by various objects. Therefore, in this study, we newly propose a two-step pre-trained model for detecting abnormal situation. Our methodology performs additional learning from image captioning to understand not only mere objects but also the complicated situation created by them. Specifically, the proposed methodology transfers knowledge of the pre-trained model that has learned object classification with ImageNet data to the image captioning model, and uses the caption that describes the situation represented by the image. Afterwards, the weight obtained by learning the situational characteristics through images and captions is extracted and fine-tuning is performed to generate an anomaly detection model. To evaluate the performance of the proposed methodology, an anomaly detection experiment was performed on 400 situational images and the experimental results showed that the proposed methodology was superior in terms of anomaly detection accuracy and F1-score compared to the existing traditional pre-trained model.

• Journal of the Korean Institute of Gas
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• v.25 no.2
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• pp.64-71
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• 2021

Research on polymer matrix composites with excellent molding processability and mechanical properties in the automotive field including hydrogen fuel cell electric vehicles is expanding to Computer-Aided Engineering (CAE) to support the design of materials with specific mechanical properties. CAE automation requires the prediction of the mechanical properties and behavior of materials. Unlike single materials, the mechanical properties prediction of polymer matrix composites is difficult to explain with formulas because the mechanical behavior is complicated to be explained only by the relationship between the matrix and the filler. In this study, the stress-strain curve according to the composition of polymer matrix composites, which was difficult to predict due to its sensitivity to large plastic deformation and composition, was predicted based on machine learning of the test data. The developed model finds a complex correlation between matrix and filler types and compositions, and predicts the total stress-strain curve meaningfully even in the absence of learned test data. It is expected that the material design AI system can be completed in the future based on the developed model that predicts the mechanical properties of polymer matrix composites even for the combination and composition that have not been learned.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.2
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• pp.307-313
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• 2022

As the development of renewable energy expands internationally to cope with global warming and climate change, the share of wind power generation has been gradually increasing. Although wind farms can produce electric power for 24 h a day compared to solar power plants, Their interfere with the operation of nearby radars or communication equipment must be analyzed because large-scale wind power turbines are installed. This study analyzed whether a land radio station can receive sufficient signals when a ship sailing outside the offshore wind farm transmits distress signals on the VHF band. Based on the geographic information system digital map around the target area, wind turbine CAD model, and wind farm layout, the area of interest and wind farm were modeled to enable numerical analysis. Among the high frequency analysis techniques suitable for radio wave analysis in a wide area, a dedicated program applying physical optics (PO) and shooting and bouncing ray (SBR) techniques were used. Consequently, the land radio station could receive the electromagnetic field above the threshold of the VHF receiver when a ship outside the offshore wind farm transmitted a distress communication signal. When the line of sight between the ships and the land station are completely blocked, the strength of the received field decreases, but it is still above the threshold. Hence, although a wind farm is a huge complex, a land station can receive the electromagnetic field from the ship's VHF transmitter because the wave length of the VHF band is sufficiently long to have effects such as diffraction or reflection.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.5
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• pp.587-599
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• 2023

As climate change increasesthe frequency and risk of flooding in major cities around theworld, the importance ofsimulation technology that can quickly and accurately analyze high-resolution 2D flooding information in large-scale areasis emerging. The physically-based approaches based on the Shallow Water Equations (SWE) often requires huge computer resources hindering high-resolution flood prediction. This study investigated the theoretical background of Weighted Cellular Automata 2D (WCA2D), which simulates spatio-temporal changes offlooding using transition rules and weight-based system, and assessed feasibility to simulate pluvial flooding in the urbancatchment, theOncheon-cheon catchmentinBusan, SouthKorea.Inaddition,the computation performancewas compared by applying versions using OpenComputing Language (OpenCL) andOpenMulti-Processing (OpenMP) parallel computing techniques. Simulationresultsshowed that the maximuminundation depthmap by theWCA2Dmodel cansimilarly reproduce historical inundation maps. Also, it can precisely simulate spatio-temporal changes of flooding extent in the urban catchment with complex topographic characteristics. For computation efficiency, parallel computing schemes, theOpenCLandOpenMP, improved the computation by about 8~14 and 5~6 folds respectively, compared to the sequential computation.