• Journal of the Korea Institute of Information Security & Cryptology
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• v.13 no.6
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• pp.121-127
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• 2003

The threshold value of the traitor-tracing schemes means a maximum number of traitors whose identities can be uniquely exposed using the tracing scheme. In the traitor-tracing scheme based on an error-correcting code, which is focused at this paper, the threshold value is determined by the error-correcting capability of the underlying error-correcting code. Analyzed in terms of a combinatorial property of the tracing scheme is the resulting effect on the tracing scheme when the collusion size is over the threshold value, and a possibility of two disjoint groups of users making an identical unauthorized decryption key is shown.

• Journal of the Regional Association of Architectural Institute of Korea
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• v.21 no.5
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• pp.109-116
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• 2019

The Seoul city recommended that old apartments be preserved, and as part of that, it decided to preserve some of the buildings for Jamsil Jugong, which was built in 1977, and Gaepo Jugong, which was constructed in 1981. The purpose of this study was to compare and review newspaper articles with two perspectives positive and negative about how the social perception of 'apartment trace remaining' was being constructed. By looking at the meaning of keywords delivered by newspaper articles and the interaction structure between keywords through the analysis of semantic networks, we analyzed how the media is pursuing an issue on the topic of preservation of architectural cultural heritage. The analysis results confirmed that there was a clear difference between positive and negative newspaper. Positive articles dealt with utilization from the point of view of keywords linked to preservation, and negative articles showed that keywords related to the property and backlash of residents linked to the policy of the Seoul Metropolitan Government were linked, leading to high negative public opinion.

• International Journal of Computer Science & Network Security
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• v.21 no.4
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• pp.28-32
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• 2021

The article discusses the theoretical and methodological part that characterizes and assessment of the current state of the theory of GR-activity, disclosed the essence and content of the concept of GR-technologies, as well as their classification. The analysis of the system of additional education for children in the social structure, as well as the analysis of the current state of the education system is carried out. The formulation of tasks for the construction of an effective model for the use of GR-technologies in the process of developing the education system using GR-technologies

• East Asian Economic Review
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• v.24 no.4
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• pp.441-468
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• 2020

Capital inflows have a strong presence that influences destination countries' development of institutions, which can in turn help resuscitate a stopped economy and re-attract capital that was lost during crises such as the recent public health crisis. While the previous literature emphasizes the mechanism that foreign investors press or even threaten the local government for change, this paper explores empirically whether institutional improvement can be achieved through the channel that host countries voluntarily reform institutions in anticipation of potential investments predicted by the exogenous geographical and cultural characteristics of the recipient countries. Given that countries with better institutional quality can accumulate larger FDI stocks, we still find that the need for more FDI, in contrast to FPI and debt, gives higher incentives to host countries to strategically improve their institutions before seeking capital overseas. Moreover, the predicted FDI exerts more prominent impacts on institutions on constraining elite than those involved in launching a business, enforcing contracts, and protecting properties. The results imply that a long-run plan for upgrading elite constraint institutions is crucial for a post-pandemic FDI reboot.

• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.97-104
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• 2021

The authors provide characteristics of the open educational platforms, classification and quantitative analysis regarding the availability of IT courses, teaching language, thematic directions on the following platforms: Coursera, EdX, Udemy, MIT Open Course Ware, OpenLearn, Intuit, Prometheus, UoPeople, Open Learning Initiative, Open University of Maidan (OUM). The quantitative analysis results are structured and visualized by tables and diagrams. The authors propose to use open educational resources (teaching, learning or research materials that are in the public domain or released with an intellectual property license that allows free use, adaptation, and distribution) for organization of independent work; for organization of distance or correspondence training; for professional development of teachers; for possibility and expediency of author's methods dissemination in the development of their own courses and promoting them on open platforms. Post-project activities are considered in comparing the courses content of one thematic direction, as well as studying the experience of their attending on different platforms.

• Smart Structures and Systems
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• v.30 no.6
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• pp.557-569
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• 2022

Vibration-based structural health monitoring (SHM) is crucial for the dynamic maintenance of civil building structures to protect property security and the lives of the public. Analyzing these vibrations with modern artificial intelligence and deep learning (DL) methods is a new trend. This paper proposed an unsupervised deep learning method based on a convolutional autoencoder (CAE), which can overcome the limitations of conventional supervised deep learning. With the convolutional core applied to the DL network, the method can extract features self-adaptively and efficiently. The effectiveness of the method in detecting damage is then tested using a benchmark model. Thereafter, this method is used to detect damage and instant disaster events in a rubber bearing-isolated gymnasium structure. The results indicate that the method enables the CAE network to learn the intact vibrations, so as to distinguish between different damage states of the benchmark model, and the outcome meets the high-dimensional data distribution characteristics visualized by the t-SNE method. Besides, the CAE-based network trained with daily vibrations of the isolating layer in the gymnasium can precisely recover newly collected vibration and detect the occurrence of the ground motion. The proposed method is effective at identifying nonlinear variations in the dynamic responses and has the potential to be used for structural condition assessment and safety warning.

• International Journal of Advanced Culture Technology
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• v.10 no.4
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• pp.499-510
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• 2022

This study examines the reporting factors of crime against business in Korea and proposes a corresponding predictive model using machine learning. While many previous studies focused on the individual factors of theft victims, there is a lack of evidence on the reporting factors of crime against a business that serves the public good as opposed to those that protect private property. Therefore, we proposed a crime prevention model for the willingness factor of theft reporting in businesses. This study used data collected through the 2015 Commercial Crime Damage Survey conducted by the Korea Institute for Criminal Policy. It analyzed data from 834 businesses that had experienced theft during a 2016 crime investigation. The data showed a problem with unbalanced classes. To solve this problem, we jointly applied the Synthetic Minority Over Sampling Technique and the Tomek link techniques to the training data. Two prediction models were implemented. One was a statistical model using logistic regression and elastic net. The other involved a support vector machine model, tree-based machine learning models (e.g., random forest, extreme gradient boosting), and a stacking model. As a result, the features of theft price, invasion, and remedy, which are known to have significant effects on reporting theft offences, can be predicted as determinants of such offences in companies. Finally, we verified and compared the proposed predictive models using several popular metrics. Based on our evaluation of the importance of the features used in each model, we suggest a more accurate criterion for predicting var.

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.3
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• pp.75-83
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• 2022

Recent settlements and sinkhole openings in urban areas have caused social problems such as damage to roads and structures, fear of the public, and loss of property. Several studies have demonstrated that surface subsidence and sinkhole opening are greatly affected by rainfall and rainfall intensity in urban areas. In this paper, we analyzed the relationship with the characteristics of recorded rainfall data using the ground subsidence database reported in major cities. The correlations were found using sedimentation and precipitation data from 2010 to 2014. The duration and intensity of a given precipitation have evolved to obtain an effect on ground sedimentation rate (SR). The results show that the relationship between SR and precipitation is asymptotic and can be modeled by a hyperbolic equation. Through this study, it is possible to predict the occurrence of ground subsidence due to precipitation in advance.

• Advances in nano research
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• v.12 no.4
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• pp.375-386
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• 2022

Synthesis of acrylate-based dispersion resins involves many parameters including temperature, ingredients concentrations, and rate of adding ingredients. Proper controlling of these parameters results in a uniform nano-size chain of polymer on one side and elimination of hazardous residual monomer on the other side. In this study, we aim to screen the process parameters via Internet of Things (IoT) to ensure that, first, the nano-size polymeric chains are in an acceptable range to acquire high adhesion property and second, the remaining hazardous substance concentration is under the minimum value for safety of public and personnel health. In this regard, a set of experiments is conducted to observe the influences of the process parameters on the size and dispersity of polymer chain and residual monomer concentration. The obtained dataset is further used to train an Adaptive Neural network Fuzzy Inference System (ANFIS) to achieve a model that predicts these two output parameters based on the input parameters. Finally, the ANFIS will return values to the automation system for further decisions on parameter adjustment or halting the process to preserve the health of the personnel and final product consumers as well.

• Journal of Urban Science
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• v.11 no.1
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• pp.29-35
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• 2022

Waste to Energy Plant were recognized as hateful facilities, and there were many conflicts in the location due to social problems such as the NIMBY phenomenon due to problems such as damage to property in the surrounding area, odor, and image loss. Problems such as air pollution and odor are solved by the development of advanced prevention facilities such as electric dust collectors, wet cleaning systems, semi-dry reaction towers, bag filters, and catalyst towers (SCR: Selective Catalytic Reduction), and air recycling facilities in waste storage tanks. However, it is being avoided because of the perception that it is an incinerator. To resolve these conflicts, the government installs and operates resident convenience facilities to compensate residents near resource recovery facilities, provides green space and improves the environment, and supports heating expenses in accordance with the 「Waste Treatment Facility Support Act」. The purpose of this study is to derive implications through the analysis of domestic and overseas case studies for resident convenience facilities and environment improvement for the promotion of local communities in resource recovery facilities and use them as basic data for community promotion and environmental improvement when installing resource recovery facilities in the future.