• The Journal of the Korea Contents Association
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• v.8 no.5
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• pp.246-259
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• 2008

This study was to minimize the trial and error in the primary step of the C4I system(ATCIS) of the each army corps on the front line, and test the economy and efficiency was tested by reviewing related papers and the system characteristics of other countries. The relationship was researched by analyzing the collected survey data and survey data related to the user's requirement level such as the army standards, that is, commonality, timeliness, simplification, automaticity, field availability and viability, multi-stage security and interoperability, unification. The result showed that the C4I system was efficiently operated through the system reliability for the specification of the system and operation manual, maneuverability and security, adaptability of the war field and system support and management, and good education and training about system operation, and less system maintenance and supplementary element. As a result, the development plan confirmed that the continuous operator education and the construction of the maintenance, and the upgrade digitalization(C4ISR+D) with the korean characteristics based on IT of network systems, and system development of the measurement model of the operator performance must be continuously supplemented in the near future.

• Journal of Korea Spatial Information System Society
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• v.12 no.1
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• pp.18-27
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• 2010

In u-GIS environment, GeoSensor environment requires that dynamic data captured from various sensors and static information in terms of features in 2D or 3D are fused together. GeoSensors, the core of this environment, are distributed over a wide area sporadically, and are collected in any size constantly. As a result, storage space could be exceeded because of restricted memory in DSMS. To solve this kind of problems, a lot of related studies are being researched actively. There are typically 3 different methods - Random Load Shedding, Semantic Load Shedding, and Sampling. Random Load Shedding chooses and deletes data in random. Semantic Load Shedding prioritizes data, then deletes it first which has lower priority. Sampling uses statistical operation, computes sampling rate, and sheds load. However, they are not high accuracy because traditional ones do not consider spatial characteristics. In this paper 'Pre-Filtering based Post Load Shedding' are suggested to improve the accuracy of spatial query and to restrict load shedding in DSMS. This method, at first, limits unnecessarily increased loads in stream queue with 'Pre-Filtering'. And then, it processes 'Post-Load Shedding', considering data and spatial status to guarantee the accuracy of result. The suggested method effectively reduces the number of the performance of load shedding, and improves the accuracy of spatial query.

• International Journal of Highway Engineering
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• v.5 no.1 s.15
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• pp.11-18
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• 2003

Road roughness, as the key factor influencing not only drivers' ride quality and safety but also pavement deterioration, is one of the most important pavement performance indicator to be evaluated by users' subjective assessment. For this reason, a specific number of the pavement roughness has been adopted to monitor the condition of a road for pavement management systems and to evaluate the quality of newly constructed sections, however, none of the unified methodology was internationally accepted. In Korea highway network, road roughness has been used mainly to evaluate newly placed pavement by using 7.6m CP (California Profile meter) to calculate PrI (Profile Index). But this instrument is manually operated to measure road profiles by traffic closure and their interpretation depends on personal bias. Therefore, problems arisen from the manually operated instrument will be overcome by using the APL (Longitudinal Profile Analyzer) which can be operated in the speed of 80km per hour. A study was conducted to correlate the relation from both concrete and asphalt pavement between IRI (measured by APL) and PrI (measured by 7.6m CP). Test results showed that there was a good correlation between IRI and PrI.

• Journal of Internet Computing and Services
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• v.19 no.1
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• pp.37-47
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• 2018

The number of capabilities of Internet of Things (IoT) devices will exponentially grow over the next years. These devices may generate a vast amount of time-constrained data. In the context of IoT, data management should act as a layer between the objects and devices generating the data and the applications accessing the data for analysis purposes and services. In addition, most of IoT services will be content-centric rather than host centric to increase the data availability and the efficiency of data delivery. IoT will enable all the communication devices to be interconnected and make the data generated by or associated with devices or objects globally accessible. Also, fog computing keeps data and computation close to end users at the edge of network, and thus provides a new breed of applications and services to end users with low latency, high bandwidth, and geographically distributed. In this paper, we propose Edge-Fog cloud-based Hierarchical Data Delivery ($EFcHD^2$) method that effectively and reliably delivers IoT data to associated with IoT applications with ensuring time sensitivity. The proposed $EFcHD^2$ method stands on basis of fully decentralized hybrid of Edge and Fog compute cloud model, Edge-Fog cloud, and uses information-centric networking and bloom filters. In addition, it stores the replica of IoT data or the pre-processed feature data by edge node in the appropriate locations of Edge-Fog cloud considering the characteristic of IoT data: locality, size, time sensitivity and popularity. Then, the performance of $EFcHD^2$ method is evaluated through an analytical model, and is compared to fog server-based and Content-Centric Networking (CCN)-based data delivery methods.

• Journal of Digital Convergence
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• v.14 no.4
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• pp.111-128
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• 2016

The purpose of this study was to analyze domestic research trends of social learning in higher education, and find out educational implications with regard to the effectiveness of social learning. The 63 articles on social learning were finally analyzed, which were published in KCI journals. The results are as follows: Firstly, in respect of research contents, the research area of utilization and the survey methods were most frequently used in those studies. Secondly, as to the use of SNS, the analyzed studies were centralized on Facebook and Formal Structured Learning. Thirdly, as for the effectiveness of SNS, the experimental studies showed that social learning has an effective impact on the learning outcomes, learning processes, and learners' characteristics. In addition, survey studies most frequently set the independent variables as learners' characteristics and the dependent variables as participation, satisfaction, and academic achievement. This research has a significance in terms of verifying the educational implications of social learning, and providing the preliminary data to facilitate the performance for the effective social learning.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.8B
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• pp.637-646
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• 2012

Recently, Wireless Sensor Networks (WSNs) are used in many applications. When sensor nodes are deployed on special areas, where humans have any difficulties to get in, the nodes form network topology themselves. By using the sensor nodes, users are able to obtain environmental information. Due to the lack of the battery capability, sensor nodes should be efficiently managed with energy consumption in WSNs. In specific applications (e.g. in intrusion detections), intruders tend to occur unexpectedly. For the energy efficiency in the applications, an appropriate algorithm is strongly required. In this paper, we propose tree-based routing algorithm for the specific applications, which based on the intrusion detection. In addition, In order to decrease traffic density, the proposed algorithm provides enhanced method considering link cost and load balance, and it establishes efficient links amongst the sensor nodes. Simultaneously, by using the proposed scheme, parent and child nodes are (re-)defined. Furthermore, efficient routing table management facilitates to improve energy efficiency especially in the limited power source. In order to apply a realistic military environment, in this paper, we design three scenarios according to an intruder's moving direction; (1) the intruder is passing along a path where sensor nodes have been already deployed. (2) the intruders are crossing the path. (3) the intruders, who are moving as (1)'s scenario, are certainly deviating from the middle of the path. In conclusion, through the simulation results, we obtain the performance results in terms of latency and energy consumption, and analyze them. Finally, we validate our algorithm is highly able to adapt on such the application environments.

• Journal of IKEEE
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• v.23 no.3
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• pp.1096-1099
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• 2019

In this paper, we propose the protocol for construction of smart factory. The proposed protocol for construction of smart factory consists of an OPC UA Server/Client, a technology of TSN realtime communication, a NTP & PTP time synchronization protocol, a FieldBus protocol and conversion module, a technology of saving data for data transmit latency and synchronization protocol. OPC UA server/client is a system integration protocol which makes interface industrial hardware device and supports standardization which allows in all around area and also in not independent from any platform. A technology of TSN realtime communication provides an high sensitive time management and control technology in a way of sharing specific time between devices in the field of high speed network. NTP & PTP time synchronization protocol supports IEEE1588 standardization. A fieldbus protocol and conversion module provide an extendable connectivity by converting industrial protocol to OPC. A technology of saving data for data transmit latency and synchronization protocol provide a resolution function for a loss and latency of data. Results from testing agencies to assess the performance of proposed protocol for construction of smart factory, response time was 0.1367ms, synchronization time was 0.404ms, quantity of concurrent access was 100ea, quantity of interacting protocol was 5ea, data saving and synchronization was 1,000 nodes. It produced the same result as the world's highest level.

• The Korean Journal of Archival Studies
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• no.29
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• pp.35-78
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• 2011

This study is intended to recommend for acquisition methods of the theatre collection. Theatre activities is representative of the performing arts, and the Korea theatre history start from the modern history of Korea. In the meantime, theatre collections has already been lost by a lack of effort and management, and scattered most of the collections. In particular, a one-off nature and volatility of theatrical performances make future generations to enjoy the performances and to study should consult the relevant records. Therefore, collecting records can be very serious mission. In this study, theatre collections of the country which aims to collect and analyze the characteristics and type of theatre collections. Based on this information, collection scope, targets, priorities, acquisition level, method of collecting are proposed the following. First, collection scope is defined for the theatre related collections which was performed nationwide in the 1900s, the times that modern theatre was begun. The object includes related information of planning, administration, drama (script), directing, stage design, public relations, production, evaluation, personal records, biographical data, group data and space data. Second, the theatre collections are divided into records and historical records. Priority of collections object is determined by the historical value and the theatre performed by the support of public organization. Third, the acquisition level is divided into archived, mirrored, web linked and database, which is proposed by the determined levels of mandatory, recommend and discretion according to the characteristic of performance. Fourth, acquisition methods are suggested by the general acquisition methods of transfer, donation and purchase as well as the methods of copy, production, legal deposit, entry and web link etc. The acquisition of theatre collections is executed on digital-based environment, and a centralized authority control should be establishmented. And through the development of network with theatre's stakeholders and the cooperation of related organizations, theatre collections acquisition is feasible.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.104-112
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• 2021

For extrusion processes in the process industry, the need to build smart factories is increasing. However, in most extrusion production sites, the production method is continuous, and because the properties of the data are undeed, it is difficult to process the data. In order to solve this problem, we present a methodology utilizing a near field communication (NFC) sensor rather than water-based data entry. To this end, a wireless network environment was built, and a data management method was designed. A non-contact NFC method was studied for the production performance-data input method, and an analysis method was implemented using the pivot function of the Excel program. As a result, data input using NFC was automated, obtaining a quantitative effect from reducing the operator's data processing time. In addition, using the input data, we present a case where a bottleneck is improved due to quality problems.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.6
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• pp.42-57
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• 2022

This study aims to create a basic model for classifying the activity photos that urban park users shared on social media using Deep Learning through Artificial Intelligence. Regarding the social media data, photos related to urban parks were collected through a Naver search, were collected, and used for the classification model. Based on the indicators of Naturalness, Potential Attraction, and Activity, which can be used to evaluate the characteristics of urban parks, 21 classification categories were created. Urban park photos shared on Naver were collected by category, and annotated datasets were created. A custom CNN model and a transfer learning model utilizing a CNN pre-trained on the collected photo datasets were designed and subsequently analyzed. As a result of the study, the Xception transfer learning model, which demonstrated the best performance, was selected as the urban park user activity image classification model and evaluated through several evaluation indicators. This study is meaningful in that it has built AI as an index that can evaluate the characteristics of urban parks by using user-shared photos on social media. The classification model using Deep Learning mitigates the limitations of manual classification, and it can efficiently classify large amounts of urban park photos. So, it can be said to be a useful method that can be used for the monitoring and management of city parks in the future.