• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• v.9 no.2
• /
• pp.177-180
• /
• 2005

AIS needs high efficiency and safety in terms of operational management and, in the aspect of service range, it is time to minimize shadow regions through propagation evaluation of AIS transmitter. Thus this study analyzes shadow regions and the scope of propagation of waves from stations through the electric wave environment of AIS. First, this study examines the characteristics of AIS wave and draws up methods to analyze the scope of propagation of waves according to the characteristics. Second, this study finds out service regions and shadow regions of the 22 stations across the nation by analyzing the actual data based on climate and topography, Lastly, this study summarizes the results of wave conductivity evaluation and conductivity problems and proposes improvement measures.

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

• KIPS Transactions on Computer and Communication Systems
• /
• v.5 no.8
• /
• pp.197-210
• /
• 2016

Lately smartphone uasage is increasing and many Internet of Things (IoT) devices support wireless communications. Accordingly, small base stations which called femtocells are supplied to prevent saturation of existing base stations. However, unlike the original purpose of the femtocell with the advanced hacking technologies, Vulnerability such as gaining the administrator authority was discovered and this can cause serious problems such as the leakage of personal information of femtocell user. Therefore, identify security threats that may occur in the femtocell and it is necessary to ways for systematic vulnerability analysis. In this paper, We analyzed the security threats that can be generated in the femtocell and constructed a checklist for vulnerability analysis using the Threat Modeling method. Then, using the constructed checklist provides a scheme that can improve the safety of the femto cell through the actual analysis and taken the results of the femtocell vulnerabilities analysis.

• KIPS Transactions on Software and Data Engineering
• /
• v.7 no.4
• /
• pp.135-144
• /
• 2018

The domestic pigsty environment is highly vulnerable to the spread of respiratory diseases such as foot-and-mouth disease because of the small space. In order to manage this issue, a variety of studies have been conducted to automatically analyze behavior of individual pigs in a pig pen through a video surveillance system using a camera. Even though it is required to correctly segment touching pigs for tracking each pig in complex situations such as aggressive behavior, detecting the correct boundaries among touching pigs using Kinect's depth information of lower accuracy is a challenging issue. In this paper, we propose a segmentation method using motion information of the touching pigs. In addition, our proposed method can be applied for detecting tracking errors in case of tracking individual pigs in the complex environment. In the experimental results, we confirmed that the touching pigs in a pig farm were separated with the accuracy of 86%, and also confirmed that the tracking errors were detected accurately.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.19 no.11
• /
• pp.521-528
• /
• 2018

Military vehicles use run-flat wheels for emergency situations. Run-flat wheels can run required distance in a defined duration with the pressure loss tire. For the application of a run-flat system, wheels are designed in 2 pieces, including an inner rim and outer rim. These rims are assembled using clamping bolts. Clamping bolts determine the durability of military vehicle wheels because fracture of clamping bolts account for most wheel failures. For improving wheel durability, clamping bolt durability must be improved. In this study, wheel test conditions and bolt design were investigated. Existing test standards are not sufficient to conduct endurance tests. Supplementary conditions were investigated. Using these modified test conditions, the durability of wheels including clamping bolts was tested and verified. Results found the durability of wheels improved more than 168%. This study also proposes improvements in the design process of clamping bolts.

• International Area Studies Review
• /
• v.21 no.4
• /
• pp.65-83
• /
• 2017

As Global value chain(GVC) is deepening, the importance of intermediated good trade is growing in international trade issues. Such facts lead to much discussions about the relation between Global Outsourcing and pollution. This study analyzed the effect of Global outsourcing on Environment using the data including 21 industries for 2004-14. $CO_2$ intensity is used as a proxy for the environment variable and to measure Global outsourcing and I employed the method suggested by Feenstra and Hanson(1999), Amiti and Wei(2006). To examine the effect Global outsourcing on the Environment more precisely, this paper controlled the factors that can affect the environment level on the basis of the theory suggested by Copeland and Taylor(1994). In the methodology, System GMM is employed to solve endogenous problem. The results show that for overall industries, Global outsourcing effect cannot be identified and for polluting industries, the result is identical. However, Global outsourcing has a negative effect on the pollution level for China and developing countries. In other words, as Global outsourcing is increasing, the national pollution level is decreasing.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.05a
• /
• pp.108-110
• /
• 2021

Since 2015, attacks using the IoT protocol have been continuously reported. Among various IoT protocols, attackers attempt DDoS attacks using SSDP(Simple Service Discovery Protocol), and as statistics of cyber shelters, Korea has about 1 million open SSDP servers. Vulnerable SSDP servers connected to the Internet can generate more than 50Gb of traffic and the risk of attack increases gradually. Until recently, distributed denial of service attacks and distributed reflective denial of service attacks have been a security issue. Accordingly, the purpose of this study is to analyze the request packet of the existing SSDP protocol to identify an amplification attack and to avoid a response when an amplification attack is suspected, thereby preventing network load due to the occurrence of a large number of response packets due to the role of traffic reflection amplification.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2020.11a
• /
• pp.54-55
• /
• 2020

In 4th Industrial Revolution, technologies such as artificial intelligence, Internet of Things, and Big data are closely related to the maritime industry, which led to the birth of autonomous vessels. Due to the technical characteristics of the current vessel, the speed cannot be suddenly lowered, so complex communication such as the help of a tug boat, boarding of a pilot, and control of the vessel at the onshore control center is required to berth at the port. In this study, clustering analysis was used to resolve how to establish control criteria for vessels to enter port when autonomous vessels are operating. K-Means clustering was used to quantitatively stage the arrival pattern based on the accumulated AIS(Automatic Identification System) data of the incoming vessel, and the arrival phase using SOG(Speed over Ground), COG(Course over Ground), and ROT(Rate of Turn) Was divided into six phase.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2023.05a
• /
• pp.104-105
• /
• 2023

해양 관측과 위성 원격탐사를 이용하여 시공간적으로 다양하게 변하는 생태 어장 환경 및 선박 관련 자료를 획득할 수 있다. 이번 연구의 주요 목적은 야간 불빛 위성 자료를 이용하여 광범위한 해역에 대한 어선의 위치 분포를 파악하는 딥러닝 기반 모델을 제안하는 것이다. 제안한 모델의 정확성을 평가하기 위해 야간 조업 어선의 위치를 포함하고 있는 AIS(Automatic Identification System) 정보와 상호 비교 평가 하였다. 이를 위해, 먼저 AIS 자료를 획득 및 분석하는 방법을 소개한다. 해양안전종합시스템(General Information Center on Maritime Safety & Security, GICOMS)으로부터 제공받은 AIS 자료는 동적정보와 정적정보로 나뉜다. 동적 정보는 일별 자료로 구분되어있으며, 이 정보에는 해상이동업무식별번호(Maritime Mobile Service Identity, MMSI), 선박의 시간, 위도, 경도, 속력(Speed over Ground, SOG), 실침로(Course over Ground, COG), 선수방향(Heading) 등이 포함되어 있다. 정적정보는 1개의 파일로 구성되어 있으며, 선박명, 선종 코드, IMO Number, 호출부호, 제원(DimA, DimB, DimC, Dim D), 홀수, 추정 톤수 등이 포함되어 있다. 이번 연구에서는 선박의 정보에서 어선의 정보를 추출하여 비교 자료로 사용하였으며, 위성 자료는 구름의 영향이 없는 깨끗한 날짜의 영상 자료를 선별하여 사용하였다. 야간 불빛 위성 자료, 구름 정보 등을 이용하여 야간 조업 어선의 불빛을 감지하는 심층신경망(Deep Neural Network; DNN) 기반 모델을 제안하였다. 본 연구의결과는 야간 어선의 분포를 감시하고 한반도 인근 어장을 보호하는데 기여할 것으로 기대된다.

• The Journal of the Acoustical Society of Korea
• /
• v.43 no.1
• /
• pp.9-18
• /
• 2024

The importance of active sonar systems is emerging due to the quietness of underwater targets and the increase in ambient noise due to the increase in maritime traffic. However, the low signal-to-noise ratio of the echo signal due to multipath propagation of the signal, various clutter, ambient noise and reverberation makes it difficult to identify underwater targets using active sonar. Attempts have been made to apply data-based methods such as machine learning or deep learning to improve the performance of underwater target recognition systems, but it is difficult to collect enough data for training due to the nature of sonar datasets. Methods based on mathematical modeling have been mainly used to compensate for insufficient active sonar data. However, methodologies based on mathematical modeling have limitations in accurately simulating complex underwater phenomena. Therefore, in this paper, we propose a sonar signal synthesis method based on a deep neural network. In order to apply the neural network model to the field of sonar signal synthesis, the proposed method appropriately corrects the attention-based encoder and decoder to the sonar signal, which is the main module of the Tacotron model mainly used in the field of speech synthesis. It is possible to synthesize a signal more similar to the actual signal by training the proposed model using the dataset collected by arranging a simulated target in an actual marine environment. In order to verify the performance of the proposed method, Perceptual evaluation of audio quality test was conducted and within score difference -2.3 was shown compared to actual signal in a total of four different environments. These results prove that the active sonar signal generated by the proposed method approximates the actual signal.