• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.13 no.3
• /
• pp.135-144
• /
• 2003

An intrusion detection system shows different result over overall detection area according to its detection characteristics of inner detection algorithms or techniques. To expand detection areas, we requires an integrated detection which can be archived both by deploying a few detection systems which detect different detection areas and by combining their results. In addition to expand detection areas, we need to decrease the workload of security managers by false alarms and improve the correctness by minimizing false alerts which happen during the process of integration. In this paper, a method for aggregation detection use fuzzy inference to integrate a vague detection results which imply the characteristics of detection systems. Their analyzed detection characteristics are expressed as fuzzy membership functions and fuzzy rule bases which are applied through the process of fuzzy control. And, it integrate a vague decision results and minimize the number of false alerts by reflecting the characteristics of detection systems. Also it does minimize inference objects by applying thresholds decided through several experiments.

• ETRI Journal
• /
• v.42 no.1
• /
• pp.46-53
• /
• 2020

Gait analysis is an effective clinical tool across a wide range of applications. Recently, inertial measurement units have been extensively utilized for gait analysis. Effective gait analyses require good estimates of heel-strike and toe-off events. Previous studies have focused on the effective device position and type of triaxis direction to detect gait events. This study proposes an effective heel-strike and toe-off detection algorithm using a smart insole with inertial measurement units. This method detects heel-strike and toe-off events through a time-frequency analysis by limiting the range. To assess its performance, gait data for seven healthy male subjects during walking and running were acquired. The proposed heel-strike and toe-off detection algorithm yielded the largest error of 0.03 seconds for running toe-off events, and an average of 0-0.01 seconds for other gait tests. Novel gait analyses could be conducted without suffering from space limitations because gait parameters such as the cadence, stance phase time, swing phase time, single-support time, and double-support time can all be estimated using the proposed heel-strike and toe-off detection algorithm.

• Journal of Korea Multimedia Society
• /
• v.13 no.2
• /
• pp.171-178
• /
• 2010

The surveillance system in general, has been sufficiently studied in the field of wireless semiconductor using basic sensors and its study of image surveillance system mainly using camera as a sensor has especially been fully implemented. In this paper, we propose 'Intelligent Image Detection System' used by image object identification technique based on the result analysis of various researches. This 'Intelligent Image Detection System' can easily trace and judge before and after a particular incident and ensure affirmative evidence and numerous relative information. Therefore, the 'Intelligent Image Detection System' proposed in this paper can be effectively used in the lived society such as traffic management, disaster alarm system and etc.

• Journal of Korea Multimedia Society
• /
• v.23 no.2
• /
• pp.282-292
• /
• 2020

In order to minimize casualties from marine vessel accidents that occur frequently at home and abroad, it is important to ensure the safety of the passengers aboard the vessel in the event of an accident. There is an EPIRB system as a system for disaster preparedness in the marine situation currently on the market, but there is a problem that the price is very expensive. In order to overcome the cost problem, which is a disadvantage of previous system, LoRaWAN-based communication is used. LoRaWAN communication-based vessel positioning and risk detection system based on LoRaWAN communication transmits measurement data of each module using two Beacon and GPS modules to stably perform position measurement for both indoor and outdoor situations. The rider danger situation detection system can detect the safety status of the rider using the 3-axis acceleration sensor, collect data from the rider positioning system and the rider safety status detection system, and send to server using LoRa communication. When conducting communication experiments in the long-distance maritime situation and actual communication experiments using the implemented system, it was found that the two experiments showed over 90% communication success rate on average.

• Journal of Biomedical Engineering Research
• /
• v.23 no.6
• /
• pp.477-484
• /
• 2002

A pacemaker autosense algorithm with dual thresholds. one for noise or tachyarrhythmia detection (noise threshold, NT) and the other for intrinsic beat detection (sensing threshold. ST), was developed to improve the sensing performance in single pass VDD electrograms. unipolar electrograms, or atrial fibrillation detection. When a deflection in an electrogram exceeds the NT (defined as 50% of 57), the autosense algorithm with dual thresholds checks if the deflection also exceeds the ST. If it does, the autosense algorithm calculates the signal to noise ratio (SNR) of the deflection to the highest deflection detected by NT but lower than ST during the last cardiac cycle. If the SNR 2, the autosense algorithm declares an intrinsic beat detection and calculates the next ST based on the three most recent intrinsic peaks. If the SNR $\geq$2, the autosense algorithm checks the number of deflections detected by NT during the last cardiac cycle in order to determine if it is a noise detection or tachyarrhythmia detection. Usually the autosense algorithm tries to set the 57 at 37.5% of the average of the three intrinsic beats, although it changes the percentage according to event classifications. The autosense algorithm was tested through computer simulation of atrial electrograms from 5 patients obtained during EP study, to simulate a worst sensing situation. The result showed that the ST levels for autosense algorithm tracked the electrogram amplitudes properly, providing more noise immunity whenever necessary. Also, the autosense algorithm with dual thresholds achieved sensing performance as good as the conventional fixed sensitivity method that was optimized retrospectively.

• Journal of Korea Society of Industrial Information Systems
• /
• v.14 no.3
• /
• pp.22-29
• /
• 2009

In previous work, anomaly-based intrusion detection techniques have been widely used to effectively detect various intrusions into a computer. This is because the anomaly-based detection techniques can effectively handle previously unknown intrusion methods. However, most of the previous work assumed that the normal network connections are fixed. For this reason, a new network connection may be regarded as an anomalous event. This paper proposes a new anomaly detection method based on an association-mining algorithm. The proposed method is composed of two phases: intra-packet association mining and inter-packet association mining. The performances of the proposed method are comparatively verified with JAM, which is a conventional representative intrusion detection method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.05a
• /
• pp.357-358
• /
• 2021

Although many people watch the scene with multiple surveillance cameras, it is difficult to ensure that immediate action can be taken in the event of a crime. Therefore, there is a need for a "crime behavior detection system" that can analyze images in real time from multiple surveillance cameras installed in elevators, call immediate crime alerts, and track crime scenes and times effectively. In this paper, a study was conducted to detect violent scenes occurring in elevators using Scene Change Detection. For effective detection, an x2-color histogram combining color histogram and histogram was applied.

• The Bulletin of The Korean Astronomical Society
• /
• v.43 no.1
• /
• pp.41.1-41.1
• /
• 2018

We introduce a current status and future plans of Korea Microlensing Telescope Network (KMTNet) microlensing experiments, which include an observational strategy, pipeline, event-finder, and collaborations with Spitzer. The KMTNet experiments were initiated in 2015. From 2016, KMTNet observes 27 fields including 6 main fields and 21 subfields. In 2017, we have finished the DIA photometry for all 2016 and 2017 data. Thus, it is possible to do a real-time DIA photometry from 2018. The DIA photometric data is used for finding events from the KMTNet event-finder. The KMTNet event-finder has been improved relative to the previous version, which already found 857 events in 4 main fields of 2015. We have applied the improved version to all 2016 data. As a result, we find that 2597 events are found, and out of them, 265 are found in KMTNet-K2C9 overlapping fields. For increasing the detection efficiency of event-finder, we are working on filtering false events out by machine-learning method. In 2018, we plan to measure event detection efficiency of KMTNet by injecting fake events into the pipeline near the image level. Thanks to high-cadence observations, KMTNet found fruitful interesting events including exoplanets and brown dwarfs, which were not found by other groups. Masses of such exoplanets and brown dwarfs are measured from collaborations with Spitzer and other groups. Especially, KMTNet has been closely cooperating with Spitzer from 2015. Thus, KMTNet observes Spitzer fields. As a result, we could measure the microlens parallaxes for many events. Also, the automated KMTNet PySIS pipeline was developed before the 2017 Spitzer season and it played a very important role in selecting the Spitzer target. For the 2018 Spitzer season, we will improve the PySIS pipeline to obtain better photometric results.

• Journal of Astronomy and Space Sciences
• /
• v.18 no.2
• /
• pp.163-173
• /
• 2001

In this paper, space radiation environment and single event effect(SEE) have been analyzed for the KOMPSAT-2 operational orbit. As spacecraft external and internal space environment, trapped proton, SEP(solar energetic particle) and GCR(galactic cosmic ray) high energy Protons and heavy ions spectrums are analyzed. Finally, SEU and SEL rate prediction has been performed for the Intel 80386 microprocessor CPU that is planned to be used in the KOMPSAT-2. As the estimation results, under nominal operational condition, it is predicted that trapped proton and high energetic proton induced SBU effect will not occur. But, it is predicted that heavy ion induced SEU can occur several times during KOMPSAT-2 3-year mission operation. KOMPSAT-2 has been implementing system level design to mitigate SEU occurrence using processor CPU error detection function of the on-board flight software.

• Horticultural Science & Technology
• /
• v.29 no.2
• /
• pp.123-129
• /
• 2011

To identify unintended vertical gene-transfer rates from the developed transgenic plants, rapid and unequivocal techniques are needed to identify event-specific markers based on flanking sequences around the transgene and to distinguish zygosity such as homo- and hetero-zygosity. To facilitate evaluation of zygosity, a polymerase chain reaction technique was used to analyze a transgenic pepper line B20 (homozygote), P915 wild type (null zygote), and their F1 hybrids, which were used as transgene contaminated plants. First, we sequenced the 3'-flanking region of the T-DNA (1,277 bp) in the transgenic pepper event B20. Based on sequence information for the 3'- and 5'-flanking region of T-DNA provided in a previous study, a primer pair was designed to amplify full length T-DNA in B20. We successfully amplified the full length T-DNA containing 986 bp from the flanking regions of B20. In addition, a 1,040 bp PCR product, which was where the T-DNA was inserted, was amplified from P915. Finally, both full length T-DNA and the 1,040 bp fragment were simultaneously amplified in the F1 hybrids; P915 ${\times}$ B20, Pungchon ${\times}$ B20, Gumtap ${\times}$ B20. In the present study, we were able to identify zygosity among homozygous transgenic event B20, its wild type P915, and hemizygous F1 hybrids. Therefore, this novel zygosity identification technique, which is based on PCR, can be effectively used to examine gene flow for transgenic pepper event B20.