• Journal of Conservation Science
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• v.29 no.4
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• pp.395-406
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• 2013

The conservation of damaged object should be restored by the similar material with the original and they have to reversibility as possible as. The characteristics of Buddhist mural paintings composed of clay are with soft material. So far, there have been a number of researches done on filling material that reinforces cracks and exfoliation of mural painting. Based on the application of traditional materials, it was found that they are appropriate to various applications. However, only based on those research results, there are some constraints to the application in the field. In addition, there has been only a few researches done on physical characteristics of filling materials. A major issue is that there is not any standard established on various mixing ratio, which is required for treatment of mural painting. This study was carried out to understand the physical characteristics of filling materials on clay mural painting. The 1st test was conducted to analyze test specimen in twelve different conditions by varying soil mixing ratio and organic medium. The 2nd test was conducted to manufacture filling materials appropriate to the mural painting, based on the result of stable condition from the 1st test, and which was applied to treatment in field.

• Journal of Convergence Society for SMB
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• v.3 no.2
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• pp.27-32
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• 2013

Wireless Body Area Networks (WBAN) have been made possible by the emergence of small and lightweight wireless systems such as Bluetooth, enabled devices and PDAs. Antennas are an essential part of any WBAN system and due to various technical requirements and physical constraints, careful consideration of their design and deployment is needed. This paper is proposing on the design of wearable antenna as parts of clothing to serve communications functions, such as tracking and navigation in health care applications. The substrates of the wearable antennas will be made from textile materials and since it is wearable, it should have a small size, be light weight, low maintenance, and unobtrusive. This proposed paper will also investigate the influence of different parameters for wearable antenna including types of textile/substrate to ensure that the antenna design satisfies WBAN requirements. The characteristics and behavior of the antenna need to adhere to specifications set by wireless standards and system technology requirements. This means that the transmitting and receiving frequency bands of the various units need to be chosen accordingly. Since there are restrictions on the level of power to which the human body can be exposed to, the antenna as well as other RF system components must be designed to meet these restrictions. Antenna gain, which directly affects power transmitted, is a critical parameter in ensuring power levels fall within the safety guidelines and so will be of primary importance in the design. The electromagnetic interaction between WBAN antennas and devices and the human body will also be explored.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.5
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• pp.847-857
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• 2020

As IoT equipment is commercialized, Bluetooth or wireless networks will be built into general living devices such as IP cameras, door locks, cars and TVs. Security for IoT equipment is becoming more important because IoT equipment shares a lot of information through the network and collects personal information and operates the system. In addition, web-based attacks and application attacks currently account for a significant portion of cyber threats, and security experts are analyzing the vulnerabilities of cyber attacks through manual analysis to secure them. However, since it is virtually impossible to analyze vulnerabilities with only manual analysis, researchers studying system security are currently working on automated vulnerability detection systems, and Firm-AFL, published recently in USENIX, proposed a system by conducting a study on fuzzing processing speed and efficiency using a coverage-based fuzzer. However, the existing tools were focused on the fuzzing processing speed of the firmware, and as a result, they did not find any vulnerability in various paths. In this paper, we propose IoTFirmFuzz, which finds more paths, resolves constraints, and discovers more crashes by strengthening the mutation process to find vulnerabilities in various paths not found in existing tools.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.5
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• pp.42-48
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• 2016

Inundation Maps are used to predict potential areas of flooding through the signs of past flooding and flood inundation analysis for flooding expected in the future, and this has led to the development of various forms of disaster-related services by governments. However, each institution has its own individual scenarios for making maps for spatial expression. Therefore, the type of spatial information is not standardized and has many forms and structures. In this study, we attempted to design the metadata that would allow Inundation Map information to be shared and used in various fields. The international standard, ISO 19115, and the domestic standards, KS X ISO 19115, TTAS.IS - 19115 and TTAS.KO - 10.0139/R1 of TTA, were used in the design to derive an appropriate standard for comparative analysis by dividing into maintenance, constraints, metadata, spatial reference system, identification, and distribution. It is expected that inundation maps will be easier to utilize and distribute among institutions and private companies by systematically collecting and managing them through the metadata design based vector space information standard developed in this study.

• The Journal of Engineering Research
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• v.6 no.2
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• pp.11-22
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• 2004

A distributed constraint satisfaction problem (distributed CSP) is a constraint satisfaction problem(CSP) in which variables and constraints are distributed among multiple automated agents. ACSP is a problem to find a consistent assignment of values to variables. Even though the definition of a CSP is very simple, a surprisingly wide variety of AI problems can be formalized as CSPs. Similarly, various application problems in DAI (Distributed AI) that are concerned with finding a consistent combination of agent actions can be formalized as distributed CAPs. In recent years, many new backtracking algorithms for solving distributed CSPs have been proposed. But most of all, they have common drawbacks that the algorithm assumes the priority of agents is static. In this thesis, we establish a basic algorithm for solving distributed CSPs called dynamic priority search algorithm that is more efficient than common backtracking algorithms in which the priority order is static. In this algorithm, agents act asynchronously and concurrently based on their local knowledge without any global control, and have a flexible organization, in which the hierarchical order is changed dynamically, while the completeness of the algorithm is guaranteed. And we showed that the dynamic priority search algorithm can solve various problems, such as the distributed 200-queens problem, the distributed graph-coloring problem that common backtracking algorithm fails to solve within a reasonable amount of time. The experimental results on example problems show that this algorithm is by far more efficient than the backtracking algorithm, in which the priority order is static. The priority order represents a hierarchy of agent authority, i.e., the priority of decision-making. Therefore, these results imply that a flexible agent organization, in which the hierarchical order is changed dynamically, actually performs better than an organization in which the hierarchical order is static and rigid. Furthermore, we describe that the agent can be available to hold multiple variables in the searching scheme.

• Journal of Korea Multimedia Society
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• v.14 no.5
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• pp.669-680
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• 2011

R-trees are widely used in various areas such as geographical information systems, CAD systems and spatial databases in order to efficiently index multi-dimensional data. As data sets used in these areas grow in size and complexity, however, range query operations on R-tree are needed to be further faster to meet the area-specific constraints. To address this problem, there have been various research efforts to develop strategies for acceleration query processing on R-tree by using the buffer mechanism or parallelizing the query processing on R-tree through multiple disks and processors. As a part of the strategies, approaches which parallelize query processing on R-tree through Graphics Processor Units(GPUs) have been explored. The use of GPUs may guarantee improved performances resulting from faster calculations and reduced disk accesses but may cause additional overhead costs caused by high memory access latencies and low data exchange rate between GPUs and the CPU. In this paper, to address the overhead problems and to adapt GPUs efficiently, we propose a novel approach which uses a GPU as a buffer to parallelize query processing on R-tree. The use of buffer algorithm can give improved performance by reducing the number of disk access and maximizing coalesced memory access resulting in minimizing GPU memory access latencies. Through the extensive performance studies, we observed that the proposed approach achieved up to 5 times higher query performance than the original CPU-based R-trees.

• Journal of The Korean Association of Information Education
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• v.26 no.3
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• pp.187-195
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• 2022

Recently, with interest in metaverse, attempts are being made to utilize the metaverse platform in various forms. In this paper, we focused on the educational application potential of metaverse, and developed and applied a metaverse STEAM program to provide an effective learning experience to learners in non-face-to-face educational situations. The developed program utilizes Minecraft and ZEPETO, familiar to students, as metaverse learning platforms, and consists of a total of 16 lessons of 5 modules in the form of modules so that alternative classes can take place in the educational field. Through this, the learner's change in STEAM attitude and learning satisfaction were measured, and through the developed STEAM program, the learner's interest, consideration, communication, usefulness, self-concept, self-efficacy, and career choice areas significantly increased. In addition, positive results were confirmed in all areas of the learner satisfaction test related to satisfaction, interest, and overall class. In the future, considering the characteristics of the metaverse, it is necessary to break free from the constraints of time and space to communicate anew, and various learner-centered educational approaches based on a high degree of freedom and immersion should be implemented.

• Journal of the Korean Society for information Management
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• v.40 no.3
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• pp.221-244
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• 2023

Focusing on Gyeonggi Library, which is preparing Metaverse services using resident participatory budgets, we deduced the role of Metaverse suitable for metropolitan representative libraries, conducting a preliminary study and analyzing various informational resources. Subsequently, we presented a collaborative content construction and service model primarily centered around the metropolitan representative library. We conducted a survey targeting on-site librarians from metropolitan representative libraries, as well as various libraries across Gyeonggi Province and the entire nation. Through this survey, we extracted insights into the Metaverse role, content possibilities, and considerations for seamless cooperation within the scope of the metropolitan representative library. Based on the opinions of surveyed librarians, it was evident that the role of the metropolitan representative library's Metaverse should function as a tool for continuous utilization of library resources and serve as a space for the entire local community. Approximately three-fourths of the respondents expressed willingness to participate in collaborative content development. However, concerns were raised about human resource limitations, budget constraints, and excessive workloads as potential obstacles to participation. This highlighted the need for systematic support from the metropolitan representative library to address these concerns.

• Geophysics and Geophysical Exploration
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• v.26 no.3
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• pp.114-125
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• 2023

The physics-informed neural network (PINN) has been proposed to overcome the limitations of various numerical methods used to solve partial differential equations (PDEs) and the drawbacks of purely data-driven machine learning. The PINN directly applies PDEs to the construction of the loss function, introducing physical constraints to machine learning training. This technique can also be applied to wave equation modeling. However, to solve the wave equation using the PINN, second-order differentiations with respect to input data must be performed during neural network training, and the resulting wavefields contain complex dynamical phenomena, requiring careful strategies. This tutorial elucidates the fundamental concepts of the PINN and discusses considerations for wave equation modeling using the PINN approach. These considerations include spatial coordinate normalization, the selection of activation functions, and strategies for incorporating physics loss. Our experimental results demonstrated that normalizing the spatial coordinates of the training data leads to a more accurate reflection of initial conditions in neural network training for wave equation modeling. Furthermore, the characteristics of various functions were compared to select an appropriate activation function for wavefield prediction using neural networks. These comparisons focused on their differentiation with respect to input data and their convergence properties. Finally, the results of two scenarios for incorporating physics loss into the loss function during neural network training were compared. Through numerical experiments, a curriculum-based learning strategy, applying physics loss after the initial training steps, was more effective than utilizing physics loss from the early training steps. In addition, the effectiveness of the PINN technique was confirmed by comparing these results with those of training without any use of physics loss.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.5
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• pp.159-174
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• 2023

In this paper, we proposed a methodology to effectively determine the selection and prioritization of new business and innovation projects using AI technology. AI technology is a technology that can upgrade the business of companies in various industries and increase the added value of the entire industry. However, there are various constraints and difficulties in the decision-making process of selecting and implementing AI projects in the enterprise. In this paper, we propose a new methodology for prioritizing AI projects using Morphology, AHP, and TOPSIS. The proposed methodology helps prioritize AI projects by simultaneously considering the technical feasibility of AI technology and real-world user requirements. In this study, we applied the proposal methodology to a real enterprise that wanted to prioritize multiple AI projects in the HR field and evaluated the results. The results confirm the practical applicability of the methodology and suggest ways to use it to help companies make decisions about AI projects. The significance of the methodology proposed in this study is that it is a framework for prioritizing multiple AI projects considered by a company in the most reasonable way by considering both business and technical factors at the same time.