• Proceedings of the KSR Conference
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• 2006.11b
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• pp.1454-1460
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• 2006

This paper assesses communication performance using a roaming simulator when roaming occurs between onboard and ground wireless communication devices for communication based train control system (CBTC). Generally, CBTC is defined as the system regularly collecting location and speed data from each train, transmitting distance information to a train, and optimizing train speed according to train performance. When a train is moving, roaming is also performed to continuously transmit and receive train control information between the ground controller and the train. To operate CBTC, packet loss rate should be less than 1%, roaming time less than 100ms during roaming. We developed a roaming simulator to check communication performance before installing ground and onboard equipments on actual wireless sections. The roaming simulator to be introduced in this paper is for roaming simulation before conducting CBTC field test, which is the project to develop Urban Rail Signaling System Standards, being conducted in KRRI. The simulation consists of one onboard wireless communication device and three ground wireless communication devices, and the roaming simulator estimate packet loss rate occurring during roaming process of the two devices. Therefore, if you use the roaming simulator before the field test, you can predict various problems to occur in actual environment and reduce time, cost and people necessary to resolve these problems.

• Journal of the military operations research society of Korea
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• v.35 no.2
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• pp.1-14
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• 2009

During wartime, the Air Force have to plan where, and how much, and what need to be distributed to surrounding local area from a chosen central bases. Each base, which has surplus more than needed amount of a certain material collected from near area of the base, is expected to distribute such surplus to other bases in shortage of it. By sending such surplus to other bases in shortage of the material, every base may get sufficient amount of all kinds of materials needed for each base during wartime. Because number of items of materials needed in each military bases during wartime are usually quite large and the frequencies of delivery from a place to other place are also pretty large if each item is delivered from a surplus place to other places in shortage, the Head Quarter of Air Force or the Logistics Command will face to difficulty to decide a reasonable delivery plan between bases for efficient and fast allocation of all materials needed to all bases during wartime. Therefore, this study suggests a solving algorithm with an established TC (transfer center: collecting and distributing center for all materials) to solve such a distribution and transportation problem.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.9 no.6
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• pp.1619-1624
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• 2008

Recently, In order to provide ubiquitous service, we develop each middleware and interface for sensors networks, RFID(Radio Frequency IDentification) and GPS(Global Positioning System). We use GPS for the location-based services, RFID for identifying the distribution logistics services, sensor networks for collecting the context data such as temperature, humidity, barometric pressure. Recently, there is increasing the need of integrated interface for using these sensor elements complexly in agriculture and livestock, construction, medical applications and, etc. This paper developments a integrated common interface for supporting efficiently process of sensing data using RFID, GPS and sensor network. This interface have the filtering function, parsing function, queuing function, interface management function, access function and, etc. We present the integrated frame structure combined with the collected context data in GPS, RFID and sensor networks and, support the open interface for providing complex ubiquitous application systems. Therefore, this interface will be efficiently used the system using RFID, GPS and sensor network, and supported many ubiquitous application services.

• The Journal of the Korea Contents Association
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• v.19 no.9
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• pp.476-484
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• 2019

RFID yoking proof proves that a pair of tags is scanned at the same time. Since the tags scanned simultaneously by a single reader are adjacent to each other, the yoking proof is used in applications that need to check the physical proximity of tagged objects. Most of the yoking proof schemes require pre-knowledge on adjacent tags. If an error occurs in the process of collecting information about adjacent tags, all subsequent proofs will fail verification. However, there is no research that suggests specific methods for obtaining information about adjacent tags. In this study, I propose a tag proximity information acquisition scheme for a yoking proof. The proposed method consists of two steps: scanning area determination and scanning area verification. In the first step, the size and position of the area to scan tags is determined in consideration of position and transmission range of the tags. In the next step, whether tag scanning is performed within the scanning area or not is verified through reference tags of the fixed position. In analysis, I show that the determined scanning area assures acquisition of adjacent tag information and the scanning area verification detects deformation and deviation of the scanning area.

• The Korean Journal of Archival Studies
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• no.74
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• pp.155-186
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• 2022

As of 2022, the number of Internet sites for public institutions registered on the 'Government 24' website (www.gov.kr) of the Ministry of the Interior and Safety is 17,000. The direct transfer takes a lot of human and material resources and time between the records-producing institution and the records-management institution that manages websites as records. In addition, it is practically difficult for records management institutions to migrate and operate various software and application technologies required to run each website. A method of automatically collecting websites from a remote location using web crawler software is used domestically and abroad to overcome these practical limitations. This study compared the performance of the web crawler required to collect and manage public Internet websites as records remotely. The most suitable web crawler was selected through a step-by-step review of several web crawlers from previous studies and other literature. Several public agency websites were applied to compare the actual performance of the crawlers in the evaluation process. The study provides empirical and specific performance comparison information for organizations that need to choose a web crawler.

• Journal of People, Plants, and Environment
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• v.23 no.3
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• pp.347-362
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• 2020

Background and objective: It is difficult to conclusively determine the exact cause of tree defects since multiple causes are involved such as climate change, plantation, tree quality and planting time, construction, planting base, drainage, sunshine conditions, maintenance, and microclimate. The data related to landscaping construction defects are scattered or fragmented by companies and years, but not managed systematically by the defect information management system. Most of the earlier studies associated with tree defects in apartment complexes suggested defect rates after examining tree defects in the completed construction site and proposed fragmentary and subjective conclusions about the causes of defects observed in trees with high defect rates. It is proposed to continue to conduct studies on the establishment and analysis of systematic databases to identify the exact causes of tree defects and measures to improve, and the need to accumulate systematic data in the construction process where many defects arises. This study was conducted to reduce the defects of trees planted in apartment complexes. Methods: Main factors related to tree defects were subdivided based on the results of literature review and a defect investigation at the completion site, and tree history management items were selected and subdivided during the construction stage. Results: The criteria for the preparation of subdivided items were obtained, and the tree history management checklist was written for the site under actual construction and a systematic database was established. Items that are categorized based to the causes of defects include the location of nurseries, date, tree quality, site conditions, planting techniques, microclimates, and maintenance. Conclusion: This study suggested tree history management items based on the tree defects that can be identified at the construction stage and applied them to the selected study site, which differentiates this study from earlier studies. It will be necessary to conduct a comprehensive and objective time series analysis on tree defects that occur over time by continuously monitoring and collecting data after construction.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.5
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• pp.743-754
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• 2022

This paper contains the results of the development and performance evaluation of the environmental data monitoring system for the fish farm. For the hardware development, the analogue sensor is used to collect dissolved oxygen, pH, salinity, and temperature of the fish farm water, and the digital sensor is used for collecting ambient temperature, humidity, and location information via a GPS module to be sent to cloud-based Firebase DB. A set of LoRa transmitters and receivers is used as a communication module to upload the collected data. The data stored in Firebase is retrieved as a graph on a web and mobile application to monitor the environmental data changes in real-time. A notification will be delivered if the collected data is outside the determined optimal value. To evaluate the performance of the developed system, a response time from hardware modules to web and mobile applications is ranging from 6.2 to 6.85 seconds, which indicates satisfactory results.

• The Journal of the Korea Contents Association
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• v.22 no.2
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• pp.1-9
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• 2022

To provide real-time traffic conditions, crowd sourcing based traffic information services in which users directly report and share traffic conditions are being developed. However, the existing traffic information service provides limited traffic conditions because it only shares information reported by specific service participants. In this paper, we design and develop a crowd sourcing based traffic information service that provides real-time traffic conditions by collecting direct reports from users and public traffic conditions. The proposed service allows users to directly report traffic conditions by voice and text, and collects and integrates traffic conditions published by external organizations. The collected traffic conditions are provided in real time through a push service, and new traffic conditions are transmitted when the user's location changes. The proposed service can report traffic conditions and share real-time traffic conditions through an Android app.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.2
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• pp.91-100
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• 2023

The existing indoor localization method using Wi-Fi fingerprinting has a high collection cost and relatively low accuracy, thus requiring integrated correction of convergence with other technologies. This paper proposes a new method that significantly reduces collection costs compared to existing methods using Wi-Fi fingerprinting. Furthermore, it does not require labeling of data at collection and can estimate pedestrian travel paths even in large indoor spaces. The proposed pedestrian movement path estimation process is as follows. Data collection is accomplished by setting up a feature area near an indoor space intersection, moving through the set feature areas, and then collecting data without labels. The collected data are processed using Kernel Linear Discriminant Analysis (KLDA) and the valley point of the Euclidean distance value between two data is obtained within the feature space of the data. We build learning data by labeling data corresponding to valley points and some nearby data by feature area numbers, and labeling data between valley points and other valley points as path data between each corresponding feature area. Finally, for testing, data are collected randomly through indoor space, KLDA is applied as previous data to build test data, the K-Nearest Neighbor (K-NN) algorithm is applied, and the path of movement of test data is estimated by applying a correction algorithm to estimate only routes that can be reached from the most recently estimated location. The estimation results verified the accuracy by comparing the true paths in indoor space with those estimated by the proposed method and achieved approximately 90.8% and 81.4% accuracy in two experimental spaces, respectively.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.3
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• pp.93-102
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• 2023

Data processing through the cloud causes many problems, such as latency and increased communication costs in the communication process. Therefore, many researchers study edge computing in the IoT, and autonomous driving is a representative application. In indoor self-driving, unlike outdoor, GPS and traffic information cannot be used, so the surrounding environment must be recognized using sensors. An efficient autonomous driving system is required because it is a mobile environment with resource constraints. This paper proposes a machine-learning method using neural networks for autonomous driving in an indoor environment. The neural network model predicts the most appropriate driving command for the current location based on the distance data measured by the LiDAR sensor. We designed six learning models to evaluate according to the number of input data of the proposed neural networks. In addition, we made an autonomous vehicle based on Raspberry Pi for driving and learning and an indoor driving track produced for collecting data and evaluation. Finally, we compared six neural network models in terms of accuracy, response time, and battery consumption, and the effect of the number of input data on performance was confirmed.