• Journal of the Korean Geotechnical Society
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• v.38 no.7
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• pp.25-37
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• 2022

In this paper, a small-scale model testing system was developed using a series of small-scale model tests to analyze the mechanism of compaction pile formation and evaluate the quality of controlled grading aggregates proposed as an alternative material to the sand compaction pile (SCP) method and granular compaction pile (GCP). These are the most typical ground improvement methods in field practice, particularly for soft grounds. However, the SCP has faced difficulties due to the supply shortage of natural sand and the corresponding price surge of sand. The GCP is limited in marine soft grounds because of the failure occurring at the pile tip caused by excessive expansion of the deeper bulbs, leading to uneven bulb formation. The uniformity of compacted pile bulbs is critical to ensuring the bearing capacity and quality of the compaction pile. This study aims to evaluate the performance of the new material and controlled grading aggregates using small-scale model tests simulating field compaction process to investigate its potential application in comparison with SCP. The compaction piles are examined in four cases according to different materials used for compaction pile and clay strength. The compaction pile materials, which are made of sand and controlled grading aggregates, used in this study were compared to reveal the mechanism of the bulb creation. The experimental data confirm that the bulb formation quality of the traditional sand and the new material, controlled grading aggregates are comparable. The compaction pile made of controlled grading aggregates presents higher bearing capacity than that of marine sand.

• Journal of Internet Computing and Services
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• v.22 no.6
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• pp.129-140
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• 2021

The next generation mBcN should be built to cooperate with the wireless network to support hyper-speed and hyper-connectivity. In this paper, we propose a network architecture for the cooperation mBcN and 5G commercial network and architecture of the cooperative security gateway required for the cooperation. The proposed cooperative security gateway is between gNB and UPF to support LBO, SFC, and security. Our analysis shows that the proposed architecture has several advantages. First of all, user equipment connected with the mBcN can be easily connected through the 5G commercial radio network to the mBcN. Second, the military application traffic can be transmitted to mBcN without going through the 5G core network, reducing the end-to-end transmission delay without causing the traffic load on the 5G core network. In addition, the security level of the military application can effectively be maintained because the user equipment can be connected to the cooperative security gateway, and the traffic generated by the user equipment is transmitted to the mBcN without going through the 5G core network. Finally, we demonstrate that LBO, SFC, and security modules are essential functions of the proposed gateway in the 5G test-bed environment.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.393-398
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• 2022

Megacities of the Repulic of Korea(ROK) will have increased by urbanization and the fourth industrial revolution. Mgacities are absolutely the opportunity factor to make human life enriched. Simultaneously, those are the challenge foctor considering the crucial conventional threat such as massive artillery and multiple rocket launcher from the North Korea. Israel that has faced the geopolitical situation of ROK developed the Multi-layer air defense system to offset the low altitude threat from the neighboring nations. As a result, Israel substantially removed plenty of Hamas' rockes and suicidal drones in 2021. Applying Israel's concept, North Korea's low altitude threat toward the ROK's megacities can effectively be eliminated. Furthermore, this Multi-layer air defense system can be a game-changer that gets rid of the low and high altitude threat from North Korea and neighboring nations with both hyperconnected sensor-C2-shooter and artificial intelligence. Through this approach, the ROK will be able to achieve the prosperity and prowth of nation at the center of Megacities concentrated on PMESII(Politics, Military, Economy, Society, Information, and Infrastructure) factors.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.5
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• pp.1019-1034
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• 2022

Malware attacks become more prevalent in the hyper-connected society of the 4th industrial revolution. To respond to such malware, automation of malware detection using artificial intelligence technology is attracting attention as a new alternative. However, using artificial intelligence without collateral for its reliability poses greater risks and side effects. The EU and the United States are seeking ways to secure the reliability of artificial intelligence, and the government announced a reliable strategy for realizing artificial intelligence in 2021. The government's AI reliability has five attributes: Safety, Explainability, Transparency, Robustness and Fairness. We develop four elements of safety, explainable, transparent, and fairness, excluding robustness in the malware detection model. In particular, we demonstrated stable generalization performance, which is model accuracy, through the verification of external agencies, and developed focusing on explainability including transparency. The artificial intelligence model, of which learning is determined by changing data, requires life cycle management. As a result, demand for the MLops framework is increasing, which integrates data, model development, and service operations. EXE-executable malware and documented malware response services become data collector as well as service operation at the same time, and connect with data pipelines which obtain information for labeling and purification through external APIs. We have facilitated other security service associations or infrastructure scaling using cloud SaaS and standard APIs.

• Journal of the Korean Geotechnical Society
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• v.26 no.11
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• pp.17-28
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• 2010

Vertical drains are commonly used to accelerate the consolidation process of soft soils, such as dredged materials, because they additionally provide a radial drainage path in a deep soil deposit. In practice, vertical drains are commonly installed in the process of self-weight consolidation of a dredged soil deposit. The absence of an appropriate analysis tool for this situation makes it substantially difficult to estimate self-weight consolidation behavior considering both vertical and radial drainage. In this paper, a new method has been proposed to take into account both vertical and radial drainage conditions during nonlinear finite strain self-weight consolidation of dredged soil deposits. For 1-D nonlinear finite strain consolidation in the vertical direction, the Morris (2002) theory and the PSDDF analysis are adopted, respectively. On the other hand, to consider the radial drainage, Barron's vertical drain theory (1948) is used. The overall average degree of self-weight consolidation of the dredged soil is estimated using the Carillo formula (1942), in which both vertical and radial drainage are assembled together. A series of large-scale self-weight consolidation experiments being equipped with a vertical drain have been carried out to verify the analysis method proposed in this paper. The results of the new analysis method were generally in agreement with those of the experiments.

• Journal of the Korean Geotechnical Society
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• v.26 no.6
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• pp.71-85
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• 2010

Dynamic analyses of tunnels are widely performed in practice in Korea. Accurate performance of a dynamic analysis is very difficult, requiring appropriate application of lower and lateral boundary conditions, deconvolution, constitutive model, and selection of dynamic soil properties etc. Lack of a systematic guideline on how to perform the dynamic analysis makes it even more difficult to perform an analysis. In addition, dynamic analyses are not needed in most cases and pseudo-static analyses are more than adequate. However, they are performed without a clear understanding on the need for the dynamic analysis and differences between the two methods. In this study, firstly, a guideline for correctly performing a 2D dynamic analysis is developed. Secondly, the differences in the tunnel responses using dynamic and pseudo-static analyses are discussed and compared. The results show that the discrepancies between the dynamic and static analyses are not significant for most cases. It is therefore recommended that the dynamic analyses be performed at tunnel portal, very soft ground, or in cases where spatial variation of the ground motion needs to be considered in the seismic analysis of tunnels in transverse direction.

• Korean Journal of Social Welfare
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• v.69 no.4
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• pp.41-65
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• 2017

This study aimed to examine the social transition, which is often metaphorized as the Fourth Industrial Revolution, within the context of social work practice and to explore measures to improve social work practice in such transition. Four social welfare researchers held seven discussions to predict the social changes in the near future centered on the Fourth Industrial Revolution and find the corresponding development strategies in social work practice; collective autobiography method was used to analyze the discussion. The analysis ascertained hyper connectivity, the advent and expansion of new communities, diversification and individualization, and the emergence of new criteria for the assessment of one's quality of life as the distinctive qualities of the near future. It was analyzed that humans and organic materials will be interconnected through spatial and temporal transcendence and that humans liberated from labor will seek for diverse communities while the number of atomized individual will increase simultaneously. Furthermore, the rise of new order of life accompanied by both the expansion of diversification and individualization and the ecological worldview brought forth by post materialistic trend was predicted. Meanwhile, the disengagement from macroscopic context, a biased inclination towards technique orientated professionalism, and individualistic social work practices without integrity were identified as the limitations of the current social work practice. This study presented three goals for social work practice to help it overcome its current shortcomings and correspond to the social changes: first, the rearrangement of practice knowledge, technique, and value so that it is based on humans and society, which are the essence of social practice work; second, the practice, such as sharing economy, that expands the individuals' boundaries of life to the community; three, the restoration of the desirability of professional social works by examining its special nature.

• Convergence Security Journal
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• v.22 no.4
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• pp.85-97
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• 2022

With the development of big data technology, data is rapidly entering a hyperconnected intelligent society that accelerates innovative growth in all industries. The convergence industry, which holds and utilizes various high-quality data, is becoming a new growth engine, and big data is fused to various traditional industries. In particular, in the medical field, structured data such as electronic medical record data and unstructured medical data such as CT and MRI are used together to increase the accuracy of disease prediction and diagnosis. Currently, the importance and size of unstructured data are increasing day by day in the medical industry, but conventional data security technologies and policies are structured data-oriented, and considerations for the security and utilization of unstructured data are insufficient. In order for medical treatment using big data to be activated in the future, data diversity and security must be internalized and organically linked at the stage of data construction, distribution, and utilization. In this paper, the current status of domestic and foreign data security systems and technologies is analyzed. After that, it is proposed to add unstructured data-centered de-identification technology to the guidelines for unstructured data and technology application cases in the industry so that unstructured data can be actively used in the medical field, and to establish standards for judging personal information for unstructured data. Furthermore, an object feature-based identification ID that can be used for unstructured data without infringing on personal information is proposed.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.137-144
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• 2023

Cyberattack technology is evolving to an unpredictable degree, and it is a situation that can happen 'at any time' rather than 'someday'. Infrastructure that is becoming hyper-connected and global due to cloud computing and the Internet of Things is an environment where cyberattacks can be more damaging than ever, and cyberattacks are still ongoing. Even if damage occurs due to external influences such as cyberattacks or natural disasters, intelligent self-recovery must evolve from a cyber resilience perspective to minimize downtime of cyber assets (OS, WEB, WAS, DB). In this paper, we propose an intelligent self-recovery technology to ensure sustainable cyber resilience when cyber assets fail to function properly due to a cyberattack. The original and updated history of cyber assets is managed in real-time using timeslot design and snapshot backup technology. It is necessary to secure technology that can automatically detect damage situations in conjunction with a commercialized file integrity monitoring program and minimize downtime of cyber assets by analyzing the correlation of backup data to damaged files on an intelligent basis to self-recover to an optimal state. In the future, we plan to research a pilot system that applies the unique functions of self-recovery technology and an operating model that can learn and analyze self-recovery strategies appropriate for cyber assets in damaged states.

• Smart Media Journal
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• v.13 no.4
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• pp.33-48
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• 2024

With the advent of 5G, characterized by Enhanced Mobile Broadband (eMBB), Ultra-Reliable Low Latency Communications (URLLC), and Massive Machine Type Communications (mMTC), efficient network management and service provision are becoming increasingly critical. This paper proposes a novel approach to address key challenges of 5G networks, namely ultra-high speed, ultra-low latency, and ultra-reliability, while dynamically optimizing network slicing and resource allocation using machine learning (ML) and deep learning (DL) techniques. The proposed methodology utilizes prediction models for network traffic and resource allocation, and employs Federated Learning (FL) techniques to simultaneously optimize network bandwidth, latency, and enhance privacy and security. Specifically, this paper extensively covers the implementation methods of various algorithms and models such as Random Forest and LSTM, thereby presenting methodologies for the automation and intelligence of 5G network operations. Finally, the performance enhancement effects achievable by applying ML and DL to 5G networks are validated through performance evaluation and analysis, and solutions for network slicing and resource management optimization are proposed for various industrial applications.