• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.6
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• pp.583-598
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• 2022

As human-based tunnel inspections are affected by the subjective judgment of the inspector, making continuous history management difficult. There is a lot of deep learning-based automatic crack detection research recently. However, the large public crack datasets used in most studies differ significantly from those in tunnels. Also, additional work is required to build sophisticated crack labels in current tunnel evaluation. Therefore, we present a method to improve crack detection performance by inputting existing datasets into a deep learning model. We evaluate and compare the performance of deep learning models trained by combining existing tunnel datasets, high-quality tunnel datasets, and public crack datasets. As a result, DeepLabv3+ with Cross-Entropy loss function performed best when trained on both public datasets, patchwise classification, and oversampled tunnel datasets. In the future, we expect to contribute to establishing a plan to efficiently utilize the tunnel image acquisition system's data for deep learning model learning.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.3
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• pp.1-7
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• 2007

RFID ( Radio Frequency IDentification ) is an automatic realization technology that recognizes things or a person with data stored tag, card, label, etc that have microchip by using radio frequency. Automation and efficient data base management(DBM) of system are possible by replaces using Bar-code that is used widely with using RFID. In this paper, we designed RFID tag data format that used to recognize information of books in Library and implemented library management system. Library management system is divided checking collection of books, self-loaning books system, self-returning books system, management books information system for a librarian. RFID leader realized information of tag and transfer it to host computer through RS-232 interface. Host computer processes and operates information with middleware. System that we made is depending on executive system for a librarian.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.12
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• pp.6434-6440
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• 2013

In this paper, an integrated control system is proposed for automatic control and remote monitoring of pipeline type UV sterilizer. The proposed system can control the cleaning wiper in the sterilizer with various cleaning motions, and periodically check the contamination level of the UV lamps with the UV power sensors. Therefore, sterilizer repair and maintenance can be more effectively done. In addition, the control system based on the open-source processor can communicate with external smart devices via Bluetooth, and thus wirelessly exchange control commands and sensor data. Furthermore, the system is able to flexibly cope with changes of cleaning motions and sensors since its firmware can be wirelessly upgraded by using the smart device. Consequently, the proposed system is suitable to construct a smart sewage treatment system in small towns.

• The Journal of Korean Association of Computer Education
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• v.5 no.1
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• pp.27-34
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• 2002

Internet has being grown explosively in recent years, hence it becomes easy to search and access information. But it is happening frequently to access illegally into the systems and data, there are many damage caused by them. So, it is very important that we construct security plan for the systems and data. It is not exception on school network being diffused to all schools. But, we have weakness about security to manage server and network safely. So it is causing much anxieties. In this paper, we searched security points make sure of safety of school network, and developed security audit agent helping management of security. Through simple registration process, this agent is able to audit basic and important security problems about not only server systems but also pc systems, and notify to administrator automatically. It is expected to provide efficiency in managing school network.

• Journal of Navigation and Port Research
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• v.45 no.1
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• pp.9-15
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• 2021

According to IMO, MASS is defined as a vessel operated at various levels independent of human interference. The safety navigation support service for MASS is designed to improve the safety and efficiency of MASS by developing public services on shore for ship arrivals/departures and for cargo handling. The safety navigation support service consists of a total of six types of services: autonomous operation, berthing/unberthing/mooring, cargo handling and ship arrival/departure service, PSC inspection, condition monitoring, and accident response support services. In order to support accident response service, the relative importance of a bridge navigational equipment was assessed by stratifying the navigation system to provide safe and efficient support services by objective judgment through specific and quantitative methods using AHP, one of decision-making methods used by an expert group. The survey was conducted by dividing the bridge navigational equipment into depth, location, and speed information. As a result of applying the AHP method, the importance of depth, location, and speed information was assessed. The relative importance of each equipment for providing location information was also assessed in order of Radar, DGPS, ECDIS, Gyro compass, Autopilot, and AIS. This was similar to survey results on the utilization of each operator's preference and its impact on marine accidents.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.5
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• pp.436-442
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• 2020

ESS(energy storage system) has recently become an important power source in various areas due to increased renewable energy resources. The more ESS is used, the less the effective capacity of the ESS. Therefore, it is important to manage the remaining useful lifetime(RUL). RUL can be checked regularly by inspectors, but it is common to be monitored and estimated by an automated monitoring system. The accurate state estimation is important to ESS operator for economical and efficient operation. RUL estimation model usually requires complex mathematical calculations consisting of cycle aging and calendar aging that are caused by the operation frequency and over time, respectively. A lightweight RUL estimation model is required to be embedded in low-performance processors that are installed on ESS. In this paper, a lightweight ESS RUL estimation model is proposed to operate on low-performance micro-processors. The simulation results show less than 1% errors compared to the original RUL model case. In addition, a performance analysis is conducted based on ATmega 328. The results show 76.8 to 78.3 % of computational time reduction.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.12
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• pp.6427-6433
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• 2013

For trains to run safely and quickly, the train should always follow the preceding train at a proper spacing. For this purpose, a certain distance between the stations is set for each block section. For the safe operation of trains in one block section, only one train service for an automatic block system is needed. The existing block system is composed an ABS, which is a linked track circuit and line sideway system through the interlocking system. The interlocking system is being replaced with a domestic electronic interlocking system. On the other hand, the block system still uses the relay format of an analog system, and is independently installed of the line sideway systems. Therefore, the existing block system has many problems in terms of construction and maintenance. In addition, the existing domestic line is used for ABS and LEU , which is installed separately, despite the train being controlled by the information of the same signal at the same location. This is not efficient in terms of each product price and the maintenance costs. This paper introduces an integrated electronic block system and the field test results. The field test was carried out through a periodic inspection performed eight times from January to late August.

• Journal of Animal Environmental Science
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• v.18 no.2
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• pp.99-110
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• 2012

The purpose of the study is to collect basis data for to establish standard administrative processes of liquid fertilizer treatment. From this survey we could make out the key point of each step through a case of effective liquid manure treatment system in pig house. It is divided into six step; 1. piggery slurry management step, 2. Solid-liquid separation step, 3. liquid fertilizer treatment (aeration) step, 4. liquid fertilizer treatment (microorganism, recirculation and internal return) step, 5. liquid fertilizer treatment (completion) step, 6. land application step. From now on, standardization process of liquid manure treatment technologies need to be develop based on the six steps process.

• Korean Journal of Comparative Education
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• v.23 no.5
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• pp.53-75
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• 2013

This article explores the impact of mergers on the experiences of students. A case design is used to gain an in-depth understanding of the students in a Korean university that was combined with a two-year college in 2007. Semi-structured interviews of 11 direct entrants, 5 transfer students, and 7 professors were conducted in 2010 for the data collection. The results suggest that mergers do not necessarily ensure the integration of the students involved. Since mergers pose enormous challenges to both transfer students and direct entrants, university leaders need to give careful attention to students' persistence and integration as the campus changes. The results also reveal that students' experience of mergers may be affected by cultural backgrounds as well as the hierarchical structure of higher education. In Korean society, where credentialism prevails, mergers can have different impacts on students who come from initial institutions of differing perceived quality, and thus mergers may incite tension among the students. In light of these concerns, this study's findings highlight the importance of student integration as a key element in mergers.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.71-84
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• 2013

Log data, which record the multitude of information created when operating computer systems, are utilized in many processes, from carrying out computer system inspection and process optimization to providing customized user optimization. In this paper, we propose a MongoDB-based unstructured log processing system in a cloud environment for processing the massive amount of log data of banks. Most of the log data generated during banking operations come from handling a client's business. Therefore, in order to gather, store, categorize, and analyze the log data generated while processing the client's business, a separate log data processing system needs to be established. However, the realization of flexible storage expansion functions for processing a massive amount of unstructured log data and executing a considerable number of functions to categorize and analyze the stored unstructured log data is difficult in existing computer environments. Thus, in this study, we use cloud computing technology to realize a cloud-based log data processing system for processing unstructured log data that are difficult to process using the existing computing infrastructure's analysis tools and management system. The proposed system uses the IaaS (Infrastructure as a Service) cloud environment to provide a flexible expansion of computing resources and includes the ability to flexibly expand resources such as storage space and memory under conditions such as extended storage or rapid increase in log data. Moreover, to overcome the processing limits of the existing analysis tool when a real-time analysis of the aggregated unstructured log data is required, the proposed system includes a Hadoop-based analysis module for quick and reliable parallel-distributed processing of the massive amount of log data. Furthermore, because the HDFS (Hadoop Distributed File System) stores data by generating copies of the block units of the aggregated log data, the proposed system offers automatic restore functions for the system to continually operate after it recovers from a malfunction. Finally, by establishing a distributed database using the NoSQL-based Mongo DB, the proposed system provides methods of effectively processing unstructured log data. Relational databases such as the MySQL databases have complex schemas that are inappropriate for processing unstructured log data. Further, strict schemas like those of relational databases cannot expand nodes in the case wherein the stored data are distributed to various nodes when the amount of data rapidly increases. NoSQL does not provide the complex computations that relational databases may provide but can easily expand the database through node dispersion when the amount of data increases rapidly; it is a non-relational database with an appropriate structure for processing unstructured data. The data models of the NoSQL are usually classified as Key-Value, column-oriented, and document-oriented types. Of these, the representative document-oriented data model, MongoDB, which has a free schema structure, is used in the proposed system. MongoDB is introduced to the proposed system because it makes it easy to process unstructured log data through a flexible schema structure, facilitates flexible node expansion when the amount of data is rapidly increasing, and provides an Auto-Sharding function that automatically expands storage. The proposed system is composed of a log collector module, a log graph generator module, a MongoDB module, a Hadoop-based analysis module, and a MySQL module. When the log data generated over the entire client business process of each bank are sent to the cloud server, the log collector module collects and classifies data according to the type of log data and distributes it to the MongoDB module and the MySQL module. The log graph generator module generates the results of the log analysis of the MongoDB module, Hadoop-based analysis module, and the MySQL module per analysis time and type of the aggregated log data, and provides them to the user through a web interface. Log data that require a real-time log data analysis are stored in the MySQL module and provided real-time by the log graph generator module. The aggregated log data per unit time are stored in the MongoDB module and plotted in a graph according to the user's various analysis conditions. The aggregated log data in the MongoDB module are parallel-distributed and processed by the Hadoop-based analysis module. A comparative evaluation is carried out against a log data processing system that uses only MySQL for inserting log data and estimating query performance; this evaluation proves the proposed system's superiority. Moreover, an optimal chunk size is confirmed through the log data insert performance evaluation of MongoDB for various chunk sizes.