• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4439-4455
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• 2021

Compared with two-stage object detection algorithms, one-stage algorithms provide a better trade-off between real-time performance and accuracy. However, these methods treat the intermediate features equally, which lacks the flexibility to emphasize meaningful information for classification and location. Besides, they ignore the interaction of contextual information from different scales, which is important for medium and small objects detection. To tackle these problems, we propose an image pyramid network based on dual attention mechanism (DAIPNet), which builds an image pyramid to enrich the spatial information while emphasizing multi-scale informative features based on dual attention mechanisms for one-stage object detection. Our framework utilizes a pre-trained backbone as standard detection network, where the designed image pyramid network (IPN) is used as auxiliary network to provide complementary information. Here, the dual attention mechanism is composed of the adaptive feature fusion module (AFFM) and the progressive attention fusion module (PAFM). AFFM is designed to automatically pay attention to the feature maps with different importance from the backbone and auxiliary network, while PAFM is utilized to adaptively learn the channel attentive information in the context transfer process. Furthermore, in the IPN, we build an image pyramid to extract scale-wise features from downsampled images of different scales, where the features are further fused at different states to enrich scale-wise information and learn more comprehensive feature representations. Experimental results are shown on MS COCO dataset. Our proposed detector with a 300 × 300 input achieves superior performance of 32.6% mAP on the MS COCO test-dev compared with state-of-the-art methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.2B
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• pp.138-147
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• 2012

With the improvement of wireless communication and embedded technology, WSN is used at various fields. Meanwhile, because WSN is resource constrained, it is more vulnerable than other networks. To solve the security problem of WSN, we can use the traditional secure mechanism like as cryptography and authentication. But the traditional secure mechanism is not enough for all security issues that may be happened in WSN, especially attacks caused by the compromised node. So, we need the IDS as the second secure mechanism for WSN. In this paper, we propose the Specification-based Intrusion Detection Mechanism that makes LEACH, which is one of the clustering routing protocol for WSN, more reliable and safety.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.7
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• pp.2614-2632
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• 2015

A multiple symbol detection (MSD) algorithm is proposed relying on soft information for ultra-wideband systems, where differential space-time block code is employed. The proposed algorithm aims to calculate a posteriori probabilities (APP) of information symbols, where a forward and backward message passing mechanism is implemented based on the BCJR algorithm. Specifically, an MSD metric is analyzed and performed for serving the APP model. Furthermore, an autocorrelation sampling is employed to exploit signals dependencies among different symbols, where the observation window slides one symbol each time. With the aid of the bidirectional message passing mechanism and the proposed sampling approach, the proposed MSD algorithm achieves a better detection performance as compared with the existing MSD. In addition, when the proposed MSD is exploited in conjunction with channel decoding, an iterative soft-input soft-output MSD approach is obtained. Finally, simulations demonstrate that the proposed approaches improve detection performance significantly.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.2
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• pp.888-894
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• 2011

Blackboard architecture was designed as a means for dealing with ill-defined and complex problems. In order to improve the efficiency of the systems using blackboard architecture, this paper proposes a mechanism for fast detection of knowledge source activations which can contribute potentially to the problem solving of blackboard systems, whenever the state of blackboard is changed. The proposed mechanism uses a Rete network generated from the activation conditions subscribed by all knowledge sources to process the pattern matching between blackboard data and the activation conditions efficiently.

• The Transactions of the Korea Information Processing Society
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• v.6 no.11
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• pp.3001-3010
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• 1999

The most of intrusion detection methods do not detect intrusion on real-time because it takes a long time to analyze an auditing data for intrusions. To solve the problem, we are studying a real-time intrusion detection. Therefore, this paper proposes an agent model using multi warning level for real-time intrusion detection. It applies to distributed environment using an extensibility and communication mechanism among agents, supports a portability, an extensibility and a confidentiality of IDS.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.857-860
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• 2009

Intrusion detection in Wireless Sensor Network (WSN) is of practical interest in many applications such as detecting an intruder in a battlefield. The intrusion detection is defined as a mechanism for a WSN to detect the existence of inappropriate, incorrect, or anomalous moving attackers. For this purpose, it is a fundamental issue to characterize the WSN parameters such as node density and sensing range in terms of a desirable detection probability. In this paper, we consider this issue according to two WSN models: homogeneous and heterogeneous WSN.

• Journal of Internet Computing and Services
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• v.3 no.5
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• pp.31-39
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• 2002

A rapid growth of internet and sudden increase of multimedia data demands for high-speed transfer media and if optimizec usage from the interface system. To achieve this level of network bandwidth, multiple NICs for support of high-speed network bandwidth have been developed and studied. Furthermore, the use of multiple NICs can provide high-speed LAN environment without large network environment modification, supports backward compatibility of current system and reduce overhead. However. if system failure is caused by SPOF(Single Point of Failure) fault of large-capacity multiple NICs, incredible loss will be met because it services large capacity of multimedia data, Therefore, to prevent loss coming from faults, we describe 'Fault tolerance of multiple NICs', which use the fault prevention mechanism. Considering inefficiency of availability and serviceability that is occurred with existing TMR, Primary-Standby approach and Watchdog time mechanism, we propose and design the efficient fault tolerance mechanism, which minimize down time as changing of detection period dynamically. Consequently, the fault tolerance mechanism proposed for reducing overhead time when the fault is occurred, should minimize system downtime overall.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.12
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• pp.1581-1587
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• 2020

With the emergence of convolutional neural network in the field of machine learning, the model for solving image processing problems has seen rapid development. However, the computing resources required are also rising, making it difficult to learn from a typical environment. Attention mechanism is originally proposed to prevent the gradient vanishing problem of the recurrent neural network, but this can also be used in a direction favorable to learning of the convolutional neural network. In this paper, attention mechanism is applied to convolutional neural network, and the excellence of the proposed method is demonstrated through the comparison of learning time and performance difference at this time. The proposed model showed that both learning time and performance were superior in object detection based on YOLO compared to models without attention mechanism, and experimentally demonstrated that learning time could be significantly reduced. In addition, this is expected to increase accessibility to machine learning by end users.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.1
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• pp.130-140
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• 2010

SIP (Session Initiation Protocol) is a signaling protocol to provide IP-based VoIP (Voice over IP) service. However, many security vulnerabilities exist as the SIP protocol utilizes the existing IP based network. The SIP Malformed message attacks may cause malfunction on VoIP services by changing the transmitted SIP header information. Additionally, there are several threats such that an attacker can extract personal information on SIP client system by inserting malicious code into SIP header. Therefore, the alternative measures should be required. In this study, we analyzed the existing research on the SIP anomaly message detection mechanism against SIP attack. And then, we proposed a Co-occurrence based SIP packet analysis mechanism, which has been used on language processing techniques. We proposed a association rule generation and an attack detection technique by using the actual SIP session state. Experimental results showed that the average detection rate was 87% on SIP attacks in case of using the proposed technique.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.7
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• pp.58-64
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• 2009

In this paper, an inspection mechanism based on laser scattering has been developed for the surface evaluation of infrared cut-off filters, and optimum conditions of laser scattering are determined using the design of experiment. First of all, attributes and influence factors of laser scattering are investigated and then a laser scattering inspection mechanism is newly designed based on analyses of laser scattering parameters. Also, Taguchi method, one of experimental designs, is used for the optimum condition selection of laser scattering parameters and the optimum condition is determined in order to maximize the detection capability of surface defects. Experiments show that the proposed method is useful in a consistent and effective defect detection and can be applied to surface evaluation processes in manufacturing.