• Journal of Information Technology Services
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• v.22 no.5
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• pp.99-108
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• 2023

As the computerization of hospitals becomes more advanced, security issues regarding data generated from various medical devices within hospitals are gradually increasing. For example, because hospital data contains a variety of personal information, attempts to attack it have been continuously made. In order to safely protect data from external attacks, each hospital has formed an internal team to continuously monitor whether the computer network is safely protected. However, there are limits to how humans can monitor attacks that occur on networks within hospitals in real time. Recently, artificial intelligence models have shown excellent performance in detecting outliers. In this paper, an experiment was conducted to verify how well an artificial intelligence model classifies normal and abnormal data in network traffic data generated from medical devices. There are several models used for outlier detection, but among them, Random Forest and Tabnet were used. Tabnet is a deep learning algorithm related to receive and classify structured data. Two algorithms were trained using open traffic network data, and the classification accuracy of the model was measured using test data. As a result, the random forest algorithm showed a classification accuracy of 93%, and Tapnet showed a classification accuracy of 99%. Therefore, it is expected that most outliers that may occur in a hospital network can be detected using an excellent algorithm such as Tabnet.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.7
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• pp.828-835
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• 2023

Vessel traffic service operators (VTSOs) need to quickly and accurately analyze the maritime traffic situation in the vessel traffic service (VTS) area and provide information to the vessels. However, if traf ic increases rapidly, the workload of VTSOs increases, and they may not be able to provide adequate information. Therefore, it is essential to develop VTSO support technologies that can reduce their workload and provide consistent information. In this paper, we propose a model for automatically detecting abnormal vessels in the VTS area. The proposed model consists of a positional model and a contextual model and is specifically optimized for the traffic characteristics of the target area. The implemented model was tested by using real-world data collected at a test center (Daesan Port VTS). Our experiments confirmed that the model could automatically detect various abnormal situations, and the results were validated through expert evaluation.

• ETRI Journal
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• v.30 no.2
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• pp.227-237
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• 2008

In this paper, an algorithm that provides absolute and proportional differentiation of packet delays is proposed with the objective of enhancing quality of service in future packet networks. It features an adaptive scheme that adjusts the target delay for every time slot to compensate the deviation from the target delay, which is caused by prediction error on the traffic to arrive at the next time slot. It predicts the traffic to arrive at the beginning of a time slot and measures the actual arrived traffic at the end of the time slot. The difference between them is utilized by the delay control operation for the next time slot to offset it. Because the proposed algorithm compensates the prediction error continuously, it shows superior adaptability to bursty traffic and exponential traffic. Through simulations we demonstrate that the algorithm meets the quantitative delay bounds and is robust to traffic fluctuation in comparison with the conventional non-adaptive mechanism. The algorithm is implemented with VHDL on a Xilinx Spartan XC3S1500 FPGA, and the performance is verified under the test board based on the XPC860P CPU.

• Journal of the Economic Geographical Society of Korea
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• v.10 no.4
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• pp.427-443
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• 2007

The purpose of this study is to investigate spacio-temporal structures of traffic flows on the subway network in the Metropolitan Seoul, and the relationships between topological structures of traffic flows and land use patterns. In particular we analyze in the topological structures of traffic flows on the subway network in time dimension as well as in spatial dimension. For the purpose, this study utilizes data mining techniques to the one day T-card transaction data of the last four years, which has developed for exploring the characteristics of traffic flows from large scale trip-transaction databases. The topological structures of traffic flows on the subway network has changed considerably during the last four years. The volumes of traffic flows, the travel time and stops per trip have increased until 2006 and decreased again in 2007. The results are visualized by utilizing GIS and analyzed, and thus the spatial patterns of traffic flows are analyzed. The spatial distribution patterns of trip origins and destinations show substantial differences among time zones during a day. We analyze the relationships between traffic flows at subway stops and the geographical variables reflecting land use around them. We obtain 6 log-linear functions from stepwise multiple regression analysis. We test multicollinearity among the variables and autocollelation for the residuals.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.12
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• pp.254-264
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• 2019

This study is a descriptive correlation study investigating the effects of stress disorder symptoms, resilience, and social network on post-traumatic growth in traffic accident patients. The participants were 158 traffic accident cases enrolled from five 100-bed hospitals situated in city C. Data were collected from July 1 to August 31, 2018, and analyzed by t-test, ANOVA, Pearson's correlation coefficients, and multiple regression using SPSS / Win23. The explanatory power of post-traumatic growth was determined to be 36.9%, and the factors affecting post-traumatic growth were social network and post-traumatic stress disorder. In addition, social networks completely established the relationship between resilience and post-traumatic growth. Our results confirmed that a wider social network and increased symptoms of post-traumatic stress disorder of the traffic accident patient are associated with higher post-traumatic growth. Therefore, it is necessary to explore approaches that improve the social networks and resilience to help post-traumatic growth of traffic accident patients. Additional research is required through repetitive and long-term observation of the accident victims.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.125-130
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• 2015

In this paper, a command and control (C2) system development using a network emulator is treated. Due to the development of information and communication technologies enabling reinforcement of information exchange and computational capability, an operational concept network centric warfare (NCW) was introduced. In here, it summarizes a developmental test environment build based on dummynet, one of the software based network emulator, and an operational concept of target command and control system. Moreover, I explain command and control system developmental test cases and results, and suggest an operational concept to overcome limitations of target communication system. I expect this concept will reduce data traffic of proposed C2 system especially plot messages which is distributed same data with short interval.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.48 no.9
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• pp.35-46
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• 2011

Future Internet should support more efficient mobility management, flexible traffic engineering and various emerging new services. So, lots of traffic engineering techniques have been suggested and developed, but it's impossible to apply them on the current running commercial Internet. To overcome this problem, OpenFlow protocol was proposed as a technique to control network equipments using network controller with various networking applications. It is a software defined network, so researchers can verify their own traffic engineering techniques by applying them on the controller. In addition, for high-speed packet processing in the OpenFlow network, programmable NetFPGA card with four 1G-interfaces and commercial Procurve OpenFlow switches can be used. In this paper, we implement an OpenFlow test-bed using hardware-accelerated NetFPGA cards and Procurve switches on the KREONET, and implement CSPF (Constraint-based Shortest Path First) algorithm, which is one of popular QoS routing algorithms, and apply it on the large-scale testbed to verify performance and efficiency of multimedia traffic engineering scheme in Future Internet.

• Journal of Broadcast Engineering
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• v.19 no.1
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• pp.14-23
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• 2014

This paper proposed controlling methods for SDN(Software Defined Network) based multiple radio access technology as the solutions of following two issues which were mainly occurred by explosive increasing of video traffic. The first one is a requirement for traffic off-loading caused by 3rd-party video service providers from the mobile network operator's viewpoint. The other one is a provision of high-speed video contents transmission services with low price. Furthermore, the performance evaluation was also conducted on the real test-bed which is composed of OpenStack cloud and SDN technology such as OpenFlow and Open vSwitch. A virtual machine running on the OpenStack provide a video service and the terminal which is able to use multiple radio access technology supports two 2.4GHz WLANs(Wireless Local Area Network) and three 5GHz WLANs, concurrently. Finally, we can get 820Mbps of the maximum transmission speed by using that five WLAN links for the single service at the same time.

• The Journal of Information Systems
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• v.29 no.2
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• pp.131-147
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• 2020

Purpose The purpose of this study is to develop intelligent vehicle parking distribution system based on LoRa network at the circumstance of traffic congestion during cultural festival in a local city. This paper proposes a parking dispatch and distribution system using a Q-learning algorithm to rapidly disperse traffics that increases suddenly because of in-bound traffics from the outside of a city in the real-time base as well as to increase parking probability in a parking lot which is widely located in a city. Design/methodology/approach The system get information on realtime-base from the sensor network of IoT (LoRa network). It will contribute to solve the sudden increase in traffic and parking bottlenecks during local cultural festival. We applied the simulation system with Queuing model to the Yudeung Festival in Jinju, Korea. We proposed a Q-learning algorithm that could change the learning policy by setting the acceptability value of each parking lot as a threshold from the Jinju highway IC (Interchange) to the 7 parking lots. LoRa Network platform supports to browse parking resource information to each vehicle in realtime. The system updates Q-table periodically using Q-learning algorithm as soon as get information from parking lots. The Queuing Theory with Poisson arrival distribution is used to get probability distribution function. The Dijkstra algorithm is used to find the shortest distance. Findings This paper suggest a simulation test to verify the efficiency of Q-learning algorithm at the circumstance of high traffic jam in a city during local festival. As a result of the simulation, the proposed algorithm performed well even when each parking lot was somewhat saturated. When an intelligent learning system such as an O-learning algorithm is applied, it is possible to more effectively distribute the vehicle to a lot with a high parking probability when the vehicle inflow from the outside rapidly increases at a specific time, such as a local city cultural festival.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.3100-3116
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• 2016

With the rapid development of urban traffic system and fast increasing of vehicle numbers, the traditional centralized ways to generate the source-destination shortest path in terms of travel time(the optimal path) encounter several problems, such as high server pressure, low query efficiency, roads state without in-time updating. With the widespread use of smart cameras in the urban traffic and surveillance system, this paper maps the optimal path finding problem in the dynamic road network to the shortest routing problem in the smart camera networks. The proposed distributed optimal path generation algorithm employs the delay routing and caching mechanism. Real-time route update is also presented to adapt to the dynamic road network. The test result shows that this algorithm has advantages in both query time and query packet numbers.