• Journal of Communications and Networks
• /
• v.16 no.2
• /
• pp.172-182
• /
• 2014

In this paper, we investigate the fundamental performance limits of the cooperative sensing using energy detection by considering the unlimited number of sensing nodes. Although a lot of cognitive radio research so far proposed various uses of energy detection because of its simplicity, the performance limits of energy detection have not been studied when a large number of sensing nodes exist. First, we show that when the sensing nodes see the independent and identically distributed channel conditions, then as the number of sensing nodes N goes to infinity, the OR rule of hard decision achieves zero of false alarm Pf for any given target probability of detection $\bar{P_d}$ irrespective of the non-zero received primary user signal to noise ratio ${\gamma}$. Second, we show that under the same condition, when the AND rule of hard decision is used, there exists a lower bound of $P_f$. Interestingly, however, for given $\bar{P_d}$, $P_f$ goes to 1 as N goes to infinity. Third, we show that when the soft decision is used, there exists a way of achieving 100% utilization of secondary user, i.e., the sensing time overhead ratio goes to zero so does $P_f$.We verify our analyses by performing extensive simulations of the proposed unlimited cooperative sensing. Finally, we suggest a way of incorporating the unlimited cooperative sensing into a practical cellular system such as long term evolutionadvanced by exploiting the existing frame structure of absolute blank subframe to implement the in-band sensing.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.41 no.9
• /
• pp.1120-1131
• /
• 2016

In this paper, we propose a smoker recognition algorithm, detecting smokers in a video sequence in order to prevent fire accidents. We use description-based method in hierarchical approaches to recognize smoker's activity, the algorithm consists of background subtraction, object detection, event search, event judgement. Background subtraction generates slow-motion and fast-motion foreground image from input image using Gaussian mixture model with two different learning-rate. Then, it extracts object locations in the slow-motion image using chain-rule based contour detection. For each object, face is detected by using Haar-like feature and smoke is detected by reflecting frequency and direction of smoke in fast-motion foreground. Hand movements are detected by motion estimation. The algorithm examines the features in a certain interval and infers that whether the object is a smoker. It robustly can detect a smoker among different objects while achieving real-time performance.

• Journal of Biomedical Engineering Research
• /
• v.38 no.4
• /
• pp.153-162
• /
• 2017

The present study proposes a system that can detect sleep-disordered breathing automatically using an air mattress and oxygen saturation. A thin air mattress was fabricated to reduce discomfort during sleep, and respiration signals were acquired. The system was configured to be synchronized with a polysomnography to receive signals simultaneously with other bio-signals. The present study has been conducted with nine adult male and female patients with sleep-disordered breathing, and sleep-disordered breathing events have been detected by applying the signals acquired from the subjects to the rule-based detection algorithm. The sensitivity and positive predictive values were found to evaluate the performance of the system, which are 91.4% and 89.7% for all events, respectively. The comparison of apnea hypopnea index(AHI) between the polysomnography and the proposed method showed squared R-value of 0.9. This study presents the possibility of detecting sleep-disordered breathing at hospitals or homes using the proposed system.

• Convergence Security Journal
• /
• v.6 no.2
• /
• pp.91-99
• /
• 2006

As the speed of network has fastened and the Internet has became common, an ill-intentioned aggression, such as worm and E-mail virus rapidly increased. So that there too many defenses created the recent Intrusion detection system as well as the Intrusion Prevention Systems to defense the malicious aggression to the network. Also as the form of malicious aggression has changed, at the same time the method of defense has changed. There is "snort" the most representive method of defense and its Rules file increases due to the change of aggression form. This causes decline of capability for detection. This paper suggest, design, and realize the structure for the improvement of processing capability by separating the files of Snort Rule according to o/s. This system show more improvement of the processing capability than the existing composion.

• Convergence Security Journal
• /
• v.15 no.4
• /
• pp.83-90
• /
• 2015

Recent, Cyber attacks such as hacking and malicious code techniques are evolving very rapidly changing cyber a ttacks are increasing, the number of malicious code techniques vary accordingly become intelligent. In the case of m alware because of the ambiguity in the number of malware have increased rapidly by name or classified as maliciou s code may have difficulty coping with. This paper investigated the naming convention of the vaccine manufacturer s in Korea to solve this problem, the analysis and offers a naming convention for security control event detection r ule analysis to compare the pattern of the detection rule out based on this current.

• Journal of the Korean Society of Safety
• /
• v.15 no.2
• /
• pp.1-7
• /
• 2000

This paper presents the approach involving fault detection and diagnosis of gears using pattern recognition and Wavelet transform. It describes result of the comparison between KDI (Kullback Discrimination Information) with the nearest neighbor classification rule as one of pattern recognition methods and Wavelet transform to know a way to detect and diagnosis of gear damages experimentally. To model the damages 1) Normal (no defect), 2) one tooth is worn out, 3) All teeth faces are worn out 4) One tooth is broken. The vibration sensor was attached on the bearing housing. This produced the total time history data that is 20 pieces of each condition. We chose the standard data and measure distance between standard and tested data. In Wavelet transform analysis method, the time series data of magnitude in specified frequency (rotary and mesh frequency) were earned. As a result, the monitoring system using Wavelet transform method and KDI with nearest neighbor classification rule successfully detected and classified the damages from the experimental data.

• Convergence Security Journal
• /
• v.8 no.4
• /
• pp.1-8
• /
• 2008

Not only the recent hacking techniques are becoming more malicious with the sophisticated technology but also its consequences are bringing more damages as the broadband Internet is growing rapidly. These may include invasion of information leakage, or identity theft over the internet. Its intent is very destructive which can result in invasion of information leakage, hacking, one of the most disturbing problems on the net. This thesis describes the technology of how you can effectively analyze and detect these kind of E-Mail malicious codes. This research explains how we can cope with malicious code more efficiently by detection method.

• IE interfaces
• /
• v.23 no.1
• /
• pp.24-34
• /
• 2010

In the telecommunication system which is based on the existing PSTN(public switched telephone network), feature interaction has been an important research issue in order to provide seamless services to users. Recently, rapid proliferation of IP-based network and the various types of IP media supply services, the feature interaction from the perspective of application services has become a significant aspect. This paper presents conflict detection and resolution algorithms for designing and operating a variety of services that are provided through IP-based network. The algorithms use explicit service interactions to detect conflicts between a new service and registered services. They then apply various rules to reduce search space in resolving conflicts. The algorithms are applied to a wide range of realistic service provision scenarios to validate that it can detect conflicts between services and resolve in accordance with different rule sets. By applying the algorithms to various scenarios, it is observed that the proposed algorithms can be effectively used in operating an IP-based services network.

• The Journal of the Acoustical Society of Korea
• /
• v.26 no.5
• /
• pp.194-198
• /
• 2007

In this paper, we apply a discriminative weight training to a statistical model-based voice activity detection(VAD). In our approach, the VAD decision rule is expressed as the geometric mean of optimally weighted likelihood ratios(LRs) based on a minimum classification error(MCE) method which is different from the previous works in that different weights are assigned to each frequency bin which is considered more realistic. According to the experimental results, the proposed approach is found to be effective for the statistical model-based VAD using the LR test.

• Journal of Korea Game Society
• /
• v.15 no.1
• /
• pp.35-44
• /
• 2015

The purpose of this study is to analyze user-generated rules in online games and to define the way of players' identities are developed. This study focuses on the online game League of Legends, which originated from use map system. Based on rule theory, this study analyzes the characteristics of user-generated rules. As the result, this study proves that the main rule of online game is not the rules made by developers, but the emergent rules made by players. Through rule-detection and rule-selection process, user-generated rules change the game system. Therefore, the result of this study expects to show meaningful roles of players in game system.