• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.1
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• pp.1-9
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• 2022

The PoN (Proof of Nonce) distributed consensus algorithm basically uses a non-competitive consensus method that can guarantee an equal opportunity for all nodes to participate in the block generation process, and this method was expected to resolve the first trilemma of the blockchain, called the decentralization problem. However, the decentralization performance of the PoN distributed consensus algorithm can be greatly affected by the network transaction transmission delay characteristics of the nodes composing the block chain system. In particular, in the consensus process, differences in network node performance may significantly affect the composition of the congress and committee on a first-come, first-served basis. Therefore, in this paper, we presented a problem by analyzing the decentralization performance of the PoN distributed consensus algorithm, and suggested a fairness control algorithm using a learning-based probabilistic acceptance rule to improve it. In addition, we verified the superiority of the proposed algorithm by conducting a numerical experiment, while considering the block chain systems composed of various heterogeneous characteristic systems with different network transmission delay.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.3
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• pp.283-290
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• 2016

Even though existing methods for orthophoto production in traditional photogrammetry are effective in large areas, they are inefficient when dealing with change detection of geometric features and image production for short time periods in small areas. In recent years, the UAV (Unmanned Aerial Vehicle), equipped with various sensors, is rapidly developing and has been implemented in various ways throughout the geospatial information field. The data and imagery of specific areas can be quickly acquired by UAVs at low costs and with frequent updates. Furthermore, the redundancy of geospatial information data can be minimized in the UAV-based orthophoto generation. In this paper, the orthophoto and DEM (Digital Elevation Model) are generated using a standard low-end UAV in small sloped areas which have a rather low accuracy compared to flat areas. The RMSE of the check points is σ_H = ±0.12 m on a horizontal plane and σ_V = ±0.09 m on a vertical plane. As a result, the maximum and mean RMSE are in accordance with the working rule agreement for the airborne laser scanning surveying of the NGII (National Geographic Information Institute) on a 1/500 scale digital map. Through this study, we verify the possibilities of the orthophoto generation in small slope areas using general-purpose low specification UAV rather than a high cost surveying UAV.

• Journal of Korean Society for Geospatial Information Science
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• v.23 no.2
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• pp.39-48
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• 2015

Lately, Unmanned Aerial Vehicles(UAV), Unmanned Aerial Systems(UAS) or also often known as drones, as a data acquisition platform and as a measurement instrument are becoming attractive for many photogrammetric surveying applications, especially generation of the high density point clouds(HDPC). This paper presents the performance evaluation of a low-cost rotary wing quadrocopter UAS for generation of the HDPC in a test bed environment. Its performance was assessed by comparing the coordinates of UAS based HDPC to the results of Network RTK GNSS surveying with 62 ground check points. The results indicate that the position RMSE of the check points are ${\sigma}_H={\pm}0.102m$ in Horizonatal plane, and ${\sigma}_V={\pm}0.209m$ in vertical, and the maxium deviation of Elevation was 0.570m within block area of ortho-photo mosaic. Therefore the required level of accuracy at NGII for production of ortho-images mosaic at a scale of 1:1000 was reached, UAS based imagery was found to make use of it to update scale 1:1000 map. And also, since this results are less than or equal to the required level in working rule agreement for airborne laser scanning surveying of NGII for Digital Elevation Model generation of grids $1m{\times}1m$ and 1:1000 scale, could be applied with production of topographic map and ortho-image mosaic at a scale of 1:1000~1:2500 over small-scale areas.

• Journal of the Society of Cosmetic Scientists of Korea
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• v.31 no.3 s.52
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• pp.265-271
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• 2005

This study is performed to investigate the effects of citrus essential oils on melanin production in B16 melanoma cells and reactive oxygen species (ROS) generation in RBL 2H3 cells. Five kinds of citrus essential oil (bergamot, grapefruit, lemmon, mandarin, petigrain) did not have any influence on DPPH radical scavenger activity, cell growth and cytotoxicity in B16 melanoma cells. In purified tyrosinase assay, both mandarin and petigrain essential oils dose-dependently inhibited its activity, but bergamot did not. In $1{\mu}M\;{\alpha}-MSH-stimulated$ B16 melanoma cells, all of 5 citrus essential oils inhibited melanin production in $\underline{a}$ dose dependent manner. On the other hand, four kinds of citrus essential oil dose-dependently increased ROS generation in RBL 2H3 mast cells, but mandarin did not. From the above results, it is possible that citrus essential oils nay be developed to be anti-melanogenic agent on the basis of their inhibitory effect on MSH-induced melanin production. Hut we can not rule out the possibility of the induction of allergy and inflammation since citrus essential oils caused ROS generation in RBL 2H3 mast cells.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.2B
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• pp.179-189
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• 2010

This paper presents a numerical investigation of vorticity generation in fully vegetated open-channel flows. The Reynolds stress model is used for the turbulence closure. Open-channel flows with rough bed-smooth sidewalls and smooth bed-rough sidewalls are simulated. The computed vectors show that in channel flows with rough bed and rough sidewalls, the free-surface secondary currents become relatively smaller and larger, respectively, compared with that of plain channel flows. Also, open-channel flows over vegetation are simulated. The computed bottom vortex occupies the entire water depth, while the free-surface vortex is reduced. The contours of turbulent anisotropy and Reynolds stress are presented with different density of vegetation. The budget analysis of vorticity equation is carried out to investigate the generation mechanism of secondary currents. The results of the budget analysis show that in plain open-channel flow, the production by anisotropy is important in the vicinity of the wall and free-surface boundaries, and the production by Reynolds stress is important in the region away from the boundaries. However, this rule is not effective in vegetated channel flows. Also, in plain channel flows, the vorticity is generated mainly in the vicinity of the free-surface and the bottom, while in vegetated channel flows, the regions of the bottom and vegetation height are important to generate the vorticity.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2006.11a
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• pp.198-203
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• 2006

Recently, the construction wastes increase rapidly due to the revitalization of reconstruction and redevelopment, the development of new urbanization of large housing development, the expansion of social infrastructure, and so on. To solve rapid increase of construction waste, the government established "the rule on the promotion of recycling of construction waste" in December, 2003. According to the rule, construction wastes can be recycled by either processing on commission or discharger of construction waste. However, most of construction waste can be recycled by processing on commission. One of the most reason is that it is difficult for proving economic effect of site recycling by discharger. This study investigated and analyzed in a generation and disposal process, status of recycling, and procedure and process of site recycling of construction waste. Also, this study proved the validation of site recycling for construction waste as economic efficiency is analyzed through the case study of site recycling at large housing development district. The results of this study can utilize the establishment of policy and basic data of feasibility for site recycling of construction waste.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.6
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• pp.1-10
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• 2005

This paper describes the implementation of HTML converter for wireless internet access in wireless application protocol environment. The implemented HTML converter consists of the contents conversion module, the conversion rule set, the WML file generation module, and the frame contents reformatting module. Plain text contents are converted to WML contents through one by one mapping, referring to the converting rule set in the contents converting module. For frame contents, the first frameset sources are parsed and the request messages are reconstructed with all the file names, reconnecting to web server as much as the number of files to receive each documents and append to the first document. Finally, after the process of reformatting in the frame contents reformatting module, frame contents are converted to WML's table contents. For image map contents, the image map related tags are parsed and the names of html documents which are linked to any sites are extracted to be replaced with WML contents data and linked to those contents. The proposed conversion method for frame contents provides a better interface for the users convenience and interactions compared to the existing converters. Conversion of image maps in our converter is one of the features not currently supported by other converters.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.1
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• pp.25-32
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• 2020

In the context-aware system, rule-based AI technology has been used in the abstraction process for getting context information. However, the rules are complicated by the diversification of user requirements for the service and also data usage is increased. Therefore, there are some technical limitations to maintain rule-based models and to process unstructured data. To overcome these limitations, many studies have applied machine learning techniques to Context-aware systems. In order to utilize this machine learning-based model in the context-aware system, a management process of periodically injecting training data is required. In the previous study on the machine learning based context awareness system, a series of management processes such as the generation and provision of learning data for operating several machine learning models were considered, but the method was limited to the applied system. In this paper, we propose a training data generating method of a machine learning model to extend the machine learning based context-aware system. The proposed method define the training data generating model that can reflect the requirements of the machine learning models and generate the training data for each machine learning model. In the experiment, the training data generating model is defined based on the training data generating schema of the cardiac status analysis model for older in health status notification service, and the training data is generated by applying the model defined in the real environment of the software. In addition, it shows the process of comparing the accuracy by learning the training data generated in the machine learning model, and applied to verify the validity of the generated learning data.

• Journal of the Korean Society for Library and Information Science
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• v.56 no.3
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• pp.241-264
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• 2022

Bibliographic metadata can help researchers effectively utilize essential publications that they need and grasp academic trends of their own fields. With the manual creation of the metadata costly and time-consuming. it is nontrivial to effectively automatize the metadata construction using rule-based methods due to the immoderate variety of the article forms and styles according to publishers and academic societies. Therefore, this study proposes a two-step extraction process based on rules and deep neural networks for generating bibliographic metadata of scientific articlles to overcome the difficulties above. The extraction target areas in articles were identified by using a deep neural network-based model, and then the details in the areas were analyzed and sub-divided into relevant metadata elements. IThe proposed model also includes a model for generating reference summary information, which is able to separate the end of the text and the starting point of a reference, and to extract individual references by essential rule set, and to identify all the bibliographic items in each reference by a deep neural network. In addition, in order to confirm the possibility of a model that generates the bibliographic information of academic papers without pre- and post-processing, we conducted an in-depth comparative experiment with various settings and configurations. As a result of the experiment, the method proposed in this paper showed higher performance.

• Journal of the Korean Society for information Management
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• v.39 no.3
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• pp.1-22
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• 2022

The purpose of this study is to propose a book recommendation system that can be used in school libraries. The book recommendation system applies an algorithm based on association rules using DLS lending data and is designed to provide personalized book recommendation services to school library users. For this purpose, association rules based on the Apriori algorithm and betweenness centrality analysis were applied and detailed functions such as descriptive statistics, generation of association rules, student-centered recommendation, and book-centered recommendation were materialized. Subsequently, opinions on the use of the book recommendation system were investigated through in-depth interviews with teacher librarians. As a result of the investigation, opinions on the necessity and difficulty of book recommendation, student responses, differences from existing recommendation methods, utilization methods, and improvements were confirmed and based on this, the following discussions were proposed. First, it is necessary to provide long-term lending data to understand the characteristics of each school. Second, it is necessary to discuss the data integration plan by region or school characteristics. Third, It is necessary to establish a book recommendation system provided by the Comprehensive Support System for Reading Education. Based on the contents proposed in this study, it is expected that various discussions will be made on the application of a personalization recommendation system that can be used in the school library in the future.