• Journal of KIISE
• /
• v.44 no.1
• /
• pp.107-113
• /
• 2017

Real-time multicasting is a packet transmission scheme ensuring that multiple destinations receive a packet within the desired time line. In wireless sensor networks, a packet can be delivered to a limited distance under a given deadline, since the end-to-end delay tends to be proportional to the end-to-end physical distance. Existing real-time multicasting protocols select the distance between the source and the furthest destination as the distance limitation and construct a multicasting tree guaranteeing delivery paths to each destination within the distance limitation. However, the protocols might lead to real-time delivery failures and energy efficiency degradation due to the fixed distance limitation. In this study, we proposed a real-time multicasting protocol using time deadline. The proposed protocol obtains the maximum transmittable distance with a given time deadline and subsequently constructs a multicasting tree using the maximum transmittable distance. The form of the multicasting tree varies according to the given time deadline to trade off the energy efficiency against the real-time delivery success ratio. The simulation results showed that the proposed scheme is superior to the existing protocols in terms of energy efficiency and real-time delivery success ratio under various time deadlines.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.4 no.1
• /
• pp.267-282
• /
• 2000

With the development of computer&network technology and the growth of its dependance, computer failures not only lose human and material resources but also make organization's competition weak as a side-effect of information society. Therefore, people consider computer security as important factor. Intrusion Detection Systems (IDS) detect intrusions and take an appropriate action against them in order to protect a computer from system failure due to illegal intrusion. A variety of methods and models for IDS have been developed until now, but the existing methods or models aren't enough to detect intrusions because of the complexity of computer network the vulnerability of the object system, insufficient understanding for information security and the appearance of new illegal intrusion method. We propose a new IDS model to be suitable at the information system organized by homogeneous hosts and design for the IDS model and implement the prototype of it for feasibility study. The IDS model consist of many distributed unit sensor IDSs at homogeneous hosts and if any of distributed unit sensor IDSs detect anomaly system call among system call sequences generated by a process, the anomaly system call can be dynamically shared with other unit sensor IDSs. This makes the IDS model can effectively detect new intruders about whole information system.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.52 no.4
• /
• pp.106-114
• /
• 2015

Despite a series of various developments in underwater acoustic sensor networks, there are still occasions of loss of connection over the network. Because sufficient amounts of drawbacks causing disconnections posed particularly in the middle of connection over the network emerge in the ocean environment, there is a need of new testing mechanism for underwater acoustic networks. In this paper, we proposed to investigate the most vital parts of the network deployment whether they function well in order, without any failure so as to identify where exactly communication process problems and failures are. We introduce step-wised out-test mechanism for UWASNS and accomplished the mechanism by implementing experiments and rigorously checked all the underwater devices utilizing out-test function. Experimental results and out-test function are evinced by implementing, in order to explain our system and conclude with possible future improvements.

• Journal of Biomedical Engineering Research
• /
• v.35 no.5
• /
• pp.119-124
• /
• 2014

A Ventricular assist device (VAD) is one of the most efficient treatments to raise the survivability of the end stage heart failure patient. However, some of LVAD patients have died for the failures and improper control of LVAD. To detect critical dangers in LVAD, the monitoring methods of LVAD outflow have been requested, because it can be affected by patient's hemodynamic states and abnormal conditions of LVAD. In the case of an external pulsatile LVAD, the air movement through the air line can be used to estimate LVAD outflow. In this study, the air movement in the air-line of the extracorporeal pulsatile LVAD was measured with a differential pressure sensor between different points. The precise estimation of air movement could be achieved by additional measurement of air pressure. In a series of in-vitro experiments, the LVAD outflow were changed according to the afterload of LVAD and the differential pressure of LVAD didn't have close correlation with the LVAD outflow that were measured with an ultrasonic flowmeter at the same time. However, new precise estimation with the data from differential pressure and one point pressure in the air-line showed higher correlations with LVAD outflow.

• Journal of the Korea Institute of Military Science and Technology
• /
• v.24 no.4
• /
• pp.457-466
• /
• 2021

This paper describes the design of model-based fault diagnosis software to apply to the propulsion system in tracked amphibious assault vehicle which consists of an engine, a transmission, a cooling system, and two waterjets. This software includes specific functions to detect the failures regarding sensor malfunctions, mechanical malfunctions, control errors, and communication errors. This software generates the proper malfunction codes which are classified as the warning and caution. In order to validate the fault diagnosis software, the manual and automatic test are performed using the test program with 32 test cases. Test results show that the designed fault diagnosis software is reliable and effective for applying to the propulsion system.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.50 no.9
• /
• pp.627-638
• /
• 2022

This paper discusses the utilization of fault-tolerant technology in the industry by analyzing the status of drone failures in the unmanned vehicle industry survey conducted in 2020. Based on the survey results of the domestic unmanned vehicle industry, we identify subsystems with high fault rates and high severity when faults occur. In addition, fault simulations of the identified subsystems are conducted to analyze the effect of the fault on the vehicles. After that, the fault diagnosis and fault compensation methods studied so far are reviewed, and research cases of the methods are examined. Moreover, the ways to apply it to actual fault cases in the unmanned vehicle industry are debated. Furthermore, based on the previous discussion, the fault-tolerant system is presented, and the consideration when designing the fault-tolerant system in the industry are studied.

• Journal of Advanced Navigation Technology
• /
• v.27 no.1
• /
• pp.111-118
• /
• 2023

For the implementation of a smart factory, it is necessary to collect data by connecting various sensors and devices in the manufacturing environment and to diagnose or predict failures in production facilities through data analysis. In this paper, to predict the residual useful lifetime of milling insert used for machining products in CNC machine, weight k-NN algorithm, Decision Tree, SVR, XGBoost, Random forest, 1D-CNN, and frequency spectrum based on vibration signal are investigated. As the results of the paper, the frequency spectrum does not provide a reliable criterion for an accurate prediction of the residual useful lifetime of an insert. And the weighted k-nearest neighbor algorithm performed best with an MAE of 0.0013, MSE of 0.004, and RMSE of 0.0192. This is an error of 0.001 seconds of the remaining useful lifetime of the insert predicted by the weighted-nearest neighbor algorithm, and it is considered to be a level that can be applied to actual industrial sites.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.23 no.2
• /
• pp.103-111
• /
• 2023

This paper proposes a new data correction technique that transforms anomalies in time series data into normal values. With the recent development of IT technology, a vast amount of time-series data is being collected through sensors. However, due to sensor failures and abnormal environments, most of time-series data contain a lot of anomalies. If we build a predictive model using original data containing anomalies as it is, we cannot expect highly reliable predictive performance. Therefore, we utilizes the LSTM-GAN model to detect anomalies in the original time series data, and combines DTW (Dynamic Time Warping) and GAN techniques to replace the anomaly data with normal data in partitioned window units. The basic idea is to construct a GAN model serially by applying the statistical information of the window with normal distribution data adjacent to the window containing the detected anomalies to the DTW so as to generate normal time-series data. Through experiments using open NAB data, we empirically prove that our proposed method outperforms the conventional two correction methods.

• Journal of Navigation and Port Research
• /
• v.48 no.1
• /
• pp.1-6
• /
• 2024

Aid-to-Navigation facility is important for maritime traffic safety. In Korea, for safe maritime traffic, the Ministry of Oceans and Fisheries is using an Aid-to-Navigation management system. The current Aid-to-Navigation management system displays information based on text, making it difficult to determine the impact if Aid-to-Navigation fails or an accident occurs. A simulator can be used to verify the placement of Aid-to-Navigation. However, real-time information is not applied and maintenance of the simulator is expensive. Additionally, the Aid-to-Navigation simulator cannot simulate effects of port backlighting. To improve these issues, we proposed an Aid-to-Navigation management platform based on digital twin technology. This system can predict failures by analyzing real-time sensor data collected from navigation signs. We plan to develop a function that can simulate Aid-to-Navigation placement. Aid-to-Navigation is expected to be managed efficiently by applying digital twin technology.

• KIPS Transactions on Software and Data Engineering
• /
• v.11 no.7
• /
• pp.299-306
• /
• 2022

In recent, sensors embedded in robots, equipment, and circuits have become common, and research for diagnosing device failures by learning measured sensor data is being actively conducted. This failure diagnosis study is divided into a classification model for predicting failure situations or types and a regression model for numerically predicting failure conditions. In the case of a classification model, it simply checks the presence or absence of a failure or defect (Class), whereas a regression model has a higher learning difficulty because it has to predict one value among countless numbers. So, the reason that regression modeling is more difficult is that there are many irregular situations in which it is difficult to determine one output from a similar input when predicting by matching input and output. Therefore, in this paper, we focus on input and output data with periodicity, analyze the input/output relationship, and secure regularity between input and output data by performing sliding window-based input data patterning. In order to apply the proposed method, in this study, current and temperature data with periodicity were collected from MMC(Modular Multilevel Converter) circuit system and learning was carried out using ANN. As a result of the experiment, it was confirmed that when a window of 2% or more of one cycle was applied, performance of 97% or more of fit could be secured.