• Journal of the Korea Society for Simulation
• /
• v.10 no.1
• /
• pp.83-92
• /
• 2001

For the prevention of the network intrusion from damaging the system, both IDS (Intrusion Detection System) and Firewall are frequently applied. The collaboration of IDS and Firewall efficiently protects the network because of making up for the weak points in the each demerit. A model has been constructed based on the DEVS (Discrete Event system Specification) formalism for the simulation of the system that consists of IDS and Firewall. With this model we can simulation whether the intrusion detection, which is a core function of IDS, is effectively done under various different conditions. As intrusions become more sophisticated, it is beyond the scope of any one IDS to deal with them. Thus we placed multiple IDS agents in the network where the information helpful for detecting the intrusions is shared among these agents to cope effectively with attackers. If an agent detects intrusions, it transfers attacker's information to a Firewall. Using this mechanism attacker's packets detected by IDS can be prevented from damaging the network.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.8 no.4
• /
• pp.107-113
• /
• 2012

Cloud computing has brought changes to the IT environment. Due to the spread of LTE, users of cloud services are growing more. This which provides IT resources to meet the needs of users of cloud services are noted as a core industry. But it is not activated because of the security of personal data and the safety of the service. In order to solve this, intrusion detection system is constructed as follows. This protects individual data safely which exists in the cloud and also protects information exhaustively from malicious attack. The cause of most attack risk which exists to cloud computing can find in distributed environment. In this study, we analyzed about necessary property of network-based intrusion detection system that process and analyze large amount of data which occur in cloud computing environment. Also, we studied functions which detect and correspond attack occurred in interior of virtualization.

• Journal of the Korea Safety Management & Science
• /
• v.14 no.4
• /
• pp.117-123
• /
• 2012

For an effective energy management in intelligent buildings it is necessary to gather information about position/absence of people and the level of population. In this paper the smart occupancy detection system using the active RFID is developed to satisfy such a demand based on the results of previous research. First of all the design considerations and functions of the system are introduced. In sequence the functions of the system is presented, and then the performance of the developed system is tested and verified through various field tests. The developed core technology can be also applied to other fields such as security, healthcare, smart home, etc.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2014.05a
• /
• pp.373-376
• /
• 2014

Shipping and logistics safety, security system is strengthening worldwide, the development of shipping and logistics safety security core technology for national security logistics system construction has been carried out. Interest in portable radiation detection device capable detecting gamma rays nuclides is increasing. In this paper, I would like to propose the study of resolution enhancement for accurate analysis of nuclides in the platform of the radiation detector portable with Cortex-A9.

• Journal of Korea Multimedia Society
• /
• v.20 no.6
• /
• pp.893-910
• /
• 2017

In this paper, we propose a simple online multiple object (human) tracking method, LKDeep (Lucas-Kanade feature and Detection based Simple Online Multiple Object Tracker), which can run in fast online enough on CPU core only with acceptable tracking performance for embedded surveillance purpose. The proposed LKDeep is a pragmatic hybrid approach which tracks multiple objects (humans) mainly based on LK features but is compensated by detection on periodic times or on necessity times. Compared to other state-of-the-art multiple object tracking methods based on 'Tracking-By-Detection (TBD)' approach, the proposed LKDeep is faster since it does not have to detect object on every frame and it utilizes simple association rule, but it shows a good object tracking performance. Through experiments in comparison with other multiple object tracking (MOT) methods using the public DPM detector among online state-of-the-art MOT methods reported in MOT challenge [1], it is shown that the proposed simple online MOT method, LKDeep runs faster but with good tracking performance for surveillance purpose. It is further observed through single object tracking (SOT) visual tracker benchmark experiment [2] that LKDeep with an optimized deep learning detector can run in online fast with comparable tracking performance to other state-of-the-art SOT methods.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.9 no.3
• /
• pp.145-150
• /
• 2014

This paper presents an effective vision based method for LED traffic light detection at the daytime. First, the proposed method calculates horizontal coordinates to set region of interest (ROI) on input sequence images. Second, the proposed uses color segmentation method to extract region of green and red traffic light. Next, to classify traffic light and another noise, shape filter and haar-like feature value are used. Finally, temporal delay filter with weight is applied to remove blinking effect of LED traffic light, and state and weight of traffic light detection are used to classify types of traffic light. For simulations, the proposed method is implemented through Intel Core CPU with 2.80 GHz and 4 GB RAM, and tested on the urban and rural road video. Average detection rate of traffic light is 94.50 % and average recognition rate of traffic type is 90.24 %. Average computing time of the proposed method is 11 ms.

• The Journal of Korea Robotics Society
• /
• v.19 no.1
• /
• pp.106-116
• /
• 2024

Ensuring robust 3D object detection is a core challenge for autonomous driving systems operating in urban environments. To tackle this issue, various 3D representation, including point cloud, voxels, and pillars, have been widely adopted, making use of LiDAR, Camera, and Radar sensors. These representations improved 3D object detection performance, but real-world urban scenarios with unexpected situations can still lead to numerous false positives, posing a challenge for robust 3D models. This paper presents a post-processing algorithm that dynamically adjusts object detection thresholds based on the distance from the ego-vehicle. While conventional perception algorithms typically employ a single threshold in post-processing, 3D models perform well in detecting nearby objects but may exhibit suboptimal performance for distant ones. The proposed algorithm tackles this issue by employing adaptive thresholds based on the distance from the ego-vehicle, minimizing false negatives and reducing false positives in the 3D model. The results show performance enhancements in the 3D model across a range of scenarios, encompassing not only typical urban road conditions but also scenarios involving adverse weather conditions.

• Steel and Composite Structures
• /
• v.50 no.1
• /
• pp.89-105
• /
• 2024

Multichannel analysis of surface waves (MASW) method has exhibited broad application prospects in the nondestructive detection of interfacial debonding in steel-concrete composite structures (SCCS). However, due to the structural diversity of SCCS and the high stealthiness of interfacial debonding defects, the feasibility of MASW method needs to be investigated in depth. In this study, synthetic parametric study on MASW nondestructive debonding detection for SCCSs is performed. The aim is to quantitatively analyze influential factors with respect to structural composition of SCCS and MASW measurement mode. First, stress wave composition and propagation process in SCCS are studied utilizing 2D numerical simulation. For structural composition in SCCS, the thickness variation of steel plate, concrete core, and debonding defects are discussed. To determine the most appropriate sensor arrangement for MASW measurement, the effects of spacing and number of observation points, along with distances between excitation points, nearest boundary, as well as the first observation point, are analyzed individually. The influence of signal type and frequency of transient excitation on dispersion figures from forwarding analysis is studied to determine the most suitable excitation signal. The findings from this study can provide important theoretical guidance for MASW-based interfacial debonding detection for SCCS. Furthermore, they can be instrumental in optimizing both the sensor layout design and signal choice for experimental validation.

• The Bulletin of The Korean Astronomical Society
• /
• v.41 no.2
• /
• pp.37.4-38
• /
• 2016

Based on the $850{\mu}m$ dust continuum data from James Clerk Maxwell Telescope (JCMT)/SCUBA-2, we compare overall properties of Planck Galactic Cold Clumps (PGCCs) in the ${\lambda}$ Orionis cloud with PGCCs in other molecular clouds, Orion A and Orion B. The Orion A and Orion B clouds are well known active star-forming region, while, ${\lambda}$ Orionis cloud has a different environment associating with prominent OB associations and a giant H II region. PGCCs in the ${\lambda}$ Orionis cloud have higher dust temperatures (Td~16.08 K) and lower values of dust emissivity (${\beta}{\sim}1.65$) than Orion A and Orion B clouds. In addition, we found the lowest detection rate (16 %, 8 out of 50) of PGCCs at $850{\mu}m$ in the ${\lambda}$ Orionis cloud while among three regions; Orion A and Orion B clouds show much higher detection rates of ~ 76 % (23 out of 30) and 56 % (9 out of 16), respectively. The detected 8 PGCCs in the ${\lambda}$ Orionis cloud have substructures and we identified 15 cores. The cores also show much lower median values of size (~0.08 pc), column density (~ ), number density (~ ), and mass (~ ) compared with other cores in the Orion A and Orion B clouds. These core properties in the ${\lambda}$ Orionis cloud can be attributed to the compression and external heating by the nearby H II region, which may prevent the PGCCs from forming gravitationally bound structures and eventually disperse them. These results well present the negative stellar feedback to core formation.

• Journal of the Korean Magnetics Society
• /
• v.23 no.5
• /
• pp.159-165
• /
• 2013

A active magnetic sensor has been widely used in the underwater guided weapon system because it is able to detect a target accurately in close range, but the target doesn't have any good countermeasure to overcome the threat from the active magnetic sensor. Recently, in order to increase the damage area of target by shock wave with explosion of the underwater weapon system and to detect small target, the maximum target detection range of the active magnetic sensor needs to be increased. One method for improving maximum target detection range is to improve output power from transmitter through demagnetization factor minimization of a transmitting core. Thus, in this paper, we describe the study results on the transmitter core shape design to enhance output power of the active magnetic sensor.