• Korean Journal of Remote Sensing
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• v.11 no.3
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• pp.49-60
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• 1995

Features of geological lineaments generally play an important role at the data interpretation concerned geological processes, mineral exploration or natural hazard risk estimation. However, there are intrinsically discordances between lineaments-related features extracted from surficial geological syrvey and those from satellite imagery;nevertheless, any data set contained those information should not be considred as less meaningful within their own task. For the purpose of effective utilization task of extracted lineaments, the mathematical scheme, based on fuzzy set theory, for practical integration of various types of rasterized data sets is studied. As a real application, the geological map named Homyeong sheet(1:50,000) and the Landset TM imageries covering same area were used, and then lineaments-related data sets such as lineaments on the geological map, lineaments extracted from a false-color image composite satellite, and major drainage pattern were utilized. For data fusion process, fuzzy membership functions of pixel values in each data set were experimentally assigned by percentile, and then fuzzy algebraic sum operator was tested. As a result, integrated lineaments by this well-known operator are regarded as newly-generated reasonable ones. Conclusively, it was thought that the implementation within available GISs, or the stand-alone module for general applications of this simple scheme can be utilized as an effective scheme can be utilized as an effective scheme for further studies for spatial integration task for providing decision-supporting information, or as a kind of spatial reasoning scheme.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.12
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• pp.485-496
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• 2018

So far, the deep learning, a field of artificial intelligence, has achieved remarkable results in solving problems from unstructured data. However, it is difficult to comprehensively judge situations like humans, and did not reach the level of intelligence that deduced their relations and predicted the next situation. Recently, deep neural networks show that artificial intelligence can possess powerful relational reasoning that is core intellectual ability of human being. In this paper, to analyze and observe the performance of Relation Networks (RN) among the neural networks for relational reasoning, two types of RN-based deep neural network models were constructed and compared with the baseline model. One is a visual question answering RN model using Sort-of-CLEVR and the other is a text-based question answering RN model using bAbI task. In order to maximize the performance of the RN-based model, various performance improvement experiments such as hyper parameters tuning have been proposed and performed. The effectiveness of the proposed performance improvement methods has been verified by applying to the visual QA RN model and the text-based QA RN model, and the new domain model using the dialogue-based LL dataset. As a result of the various experiments, it is found that the initial learning rate is a key factor in determining the performance of the model in both types of RN models. We have observed that the optimal initial learning rate setting found by the proposed random search method can improve the performance of the model up to 99.8%.

• Korean Journal of Construction Engineering and Management
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• v.20 no.3
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• pp.3-11
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• 2019

The construction of a facility is an act whereby infrastructure such as roads and railways and other facilities such as housing and office spaces are constructed, and due to the characteristics of the relevant industry where such construction is carried out in a custom order method, it requires a long period of time mostly. While the construction is carried out over a long period of time, fluctuations in the price of raw materials required for the construction occur. Therefore, the cost of the construction also fluctuates inevitably. The fluctuation of the construction cost meshes closely with the profit of a constructor and the efficiency of government spending. Therefore, it is necessary to maintain the construction cost at a reasonable level by adjusting the construction cost rationally in order to secure the required construction quality and spend the budget efficiently. The buffer system for solving such problem is the contract amount adjustment system by fluctuations in prices (Escalation/De-Escalation). In this study, the method combining the escalation method based on the item adjustment method was suggested for an efficient contract amount adjustment method. In addition, it is proposed that there be an investigation and codification of matters not applied to government acts and regulations on contracts related to the adjustment of fluctuations in prices legally.

• Journal of the Korean Society for Environmental Technology
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• v.19 no.6
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• pp.576-585
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• 2018

Systematic management during the whole life cycle from construction to operation and maintenance is very important for the seven underground pipelines (waterworks, sewerage, electricity, telecommunications, gas, heating, oil including waterworks and sewerage). Especially, it is the construction process that affects the whole life cycle of underground buried pipeline. In order to construct a new city or to maintain different underground pipes, it is always necessary to dig the ground and carry out construction and related work. There is a possibility that secondary and tertiary breaks frequently occur in the pipeline construction process after the piping constructed first in this process. To solve this problem, a system is needed which can monitor damage in real time. However, the supply of electric power for continuous operation of the system is limited according to the environment of underground buried pipelines, so it is necessary to develop a stable electric power supply system using natural energy rather than existing electric power. In this study, we developed a system that can operate the pipeline monitoring system for long time (24 hours and 15 days) using natural energy using wind and solar light.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.6
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• pp.687-695
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• 2020

Micropile is used to improve the stability of existing structures as well as solve various geotechnical problems, such as suppressing slope activity and shearing keys of retaining walls. The existing micropile method has a significantly less capacity to resist a horizontal force than a vertical force0355 Therefore, it is necessary to develop and study an umbrella-type micropile method with excellent seismic performance that can secure seismic performance economically while minimizing structures and ground disturbance areas in the limited space of existing structures. In this study, numerical analysis was performed on the umbrella-type micropile, in which the sloped pile and vertical pile were combined, and the horizontal behavior in soft clay ground during earthquakes was analyzed. Numerical analysis showed that umbrella-type micropile suppresses horizontal displacement in soft ground, and the effect of reducing the horizontal displacement was more pronounced when the embedded depth of the slope pile was 15 m or more. The embedded depth of the micropile and horizontal displacement suppression effect was proportional. Therefore, the umbrella-type micropile has an excellent effect of suppressing horizontal displacement during earthquakes on soft clay ground.

• Applied Chemistry for Engineering
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• v.25 no.2
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• pp.134-141
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• 2014

As the concerns about environmental problems, climate change and limited fossil resources increase, bio-based production of chemicals and polymers from renewable resources gains much attention as one of the promising solutions to deal with these problems. To solve these problems, much effort has been devoted to the development of sustainable process using renewable resources. Recently, many chemicals and polymers have been synthesized by biorefinery process and these bio-based chemicals and plastics have been suggested as strong candidates to substitute petroleum-based products. In this review, we discuss current advances on the development of metabolically engineered microorganisms for the efficient production of bio-based chemicals and polymers.

• Smart Media Journal
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• v.10 no.2
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• pp.61-69
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• 2021

Wayfinding is a 'Process solving problem to find destination', and it is important to select spatial data for optimal way. Recently, due to the complexity of space and the expansion of the medium of the wayfinding service, it is necessary to the approach on the information design for them. Therefore, the purpose of this study is to propose a meta guideline on the information design for the design of orientation sign, which is an important cognitive clue in the wayfinding. It was conducted in 3 stages, First, a design process was proposed and design elements were derived for each step by literature research related to information and sign design, and analysis of manual for signage design. Second, a meta guideline for information organization and visualization in the three-stage design process was proposed by FGI and analysis. Third, the meta guideline was applied to the sign design on an area for user evaluation to inspect the applicability of the meta guideline. Through the user questionnaire, the possibility of applying the guideline for visualization of directions and spaces, information hierarchy according to spatial characteristics and information priority was identified. It is meaningful in that necessary element for signage design are systematized centering on the process and that it presents a macroscopic methodology according to spatial characteristics.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.32 no.5
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• pp.191-198
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• 2022

Zirconia and titanium alloys, which are mainly used for dental implant materials, have poor osseointegration and osteogenesis abilities due to their bioinertness with low bioactivity on surface. In order to improve their surface bioinertness, surface modification with a bioactive material is an easy and simple method. In this study, akermanite (Ca₂MgSi₂O₇), a silicate-based bioceramic material with excellent bone bonding ability, was synthesized by a solid-state reaction and investigated its bioactivity from the analysis of surface dissolution and precipitation of hydroxyapatite particles in SBF solution. Calcium carbonate (CaCO₃), magnesium carbonate (MgCO₃), and silicon dioxide (SiO₂) were used as starting materials. After homogeneous mixing of starting materials by ball milling and the drying of at oven, uniaxial pressing was performed to form a compacted disk, and then heat-treated at high temperature to induce the solid-state reaction to akermanite. Bioactivity of synthesized akermanite disk was evaluated with the reaction temperature from the immersion test in SBF solution. The higher the reaction temperature, the more pronounced the akermanite phase and the less the surface dissolution at particle surface. It resulted that synthesized akermanite particles had high bioactivity on particle surface, but it depended on reacted temperature and phase composition. Moderate dissolution occurred at particle surfaces and observed the new precipitated hydroxyapatite particles in synthetic akermanite with solid-state reaction at 1100℃.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.10
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• pp.345-352
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• 2022

Recent LiDAR(Light Detection And Ranging) sensor is used for scanning object around in real-time. This sensor can detect movement of the object and how it has changed. As the production cost of the sensors has been decreased, LiDAR begins to be used for various industries such as facility guard, smart city and self-driving car. However, LiDAR has a large input data size due to its real-time scanning process. So another way for processing a large amount of data are needed in LiDAR system because it can cause a bottleneck. This paper proposes edge computing to compress massive point cloud for processing quickly. Since laser's reflection range of LiDAR sensor is limited, multiple LiDAR should be used to scan a large area. In this reason multiple LiDAR sensor's data should be processed at once to detect or recognize object in real-time. Edge computer compress point cloud efficiently to accelerate data processing and decompress every data in the main cloud in real-time. In this way user can control LiDAR sensor in the main system without any bottleneck. The system we suggest solves the bottleneck which was problem on the cloud based method by applying edge computing service.

• Journal of Korea Water Resources Association
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• v.55 no.2
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• pp.121-133
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• 2022

The drought resulting from insufficient rainfall compared to the amount in an ordinary year can significantly impact a broad area at the same time. Another feature of this disaster is hard to recognize its onset and disappearance. Therefore, a reliable and fast way of predicting both the suffering area and the amount of water shortage from the upcoming drought is a key issue to develop a countermeasure of the disaster. However, the available drought scenarios are about 50 events that have been observed in the past. Due to the limited number of events, it is difficult to predict the water shortage in a case where the pattern of a natural disaster is different from the one in the past. To overcome the limitation, in this study, we applied the four RCP climate change scenarios to the water balance model and the annual amount of water shortage from 360 drought events was estimated. In the following chapter, the deep neural network model was trained with the SPEI values from the RCP scenarios and the amount of water shortage as the input and output, respectively. The trained model in each sub-basin enables us to easily and reliably predict the water shortage with the SPEI values in the past and the predicted meteorological conditions in the upcoming season. It can be helpful for decision-makers to respond to future droughts before their onset.