• KIPS Transactions on Computer and Communication Systems
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• v.11 no.1
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• pp.23-34
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• 2022

With the development of network technology, the application area has also been diversified, and protocols for various purposes have been developed and the amount of traffic has exploded. Therefore, it is difficult for the network administrator to meet the stability and security standards of the network with the existing traditional switching and routing methods. Software Defined Networking (SDN) is a new networking paradigm proposed to solve this problem. SDN enables efficient network management by programming network operations. This has the advantage that network administrators can flexibly respond to various types of attacks. In this paper, we design a threat level management module, an attack detection module, a packet statistics module, and a flow rule generator that collects attack information through the controller and switch, which are components of SDN, and detects attacks based on these attributes of SDN. It proposes a method to block denial of service attacks (DoS) of advanced attackers by programming and applying honeypot. In the proposed system, the attack packet can be quickly delivered to the honeypot according to the modifiable flow rule, and the honeypot that received the attack packets analyzed the intelligent attack pattern based on this. According to the analysis results, the attack detection module and the threat level management module are adjusted to respond to intelligent attacks. The performance and feasibility of the proposed system was shown by actually implementing the proposed system, performing intelligent attacks with various attack patterns and attack levels, and checking the attack detection rate compared to the existing system.

• The Journal of the Acoustical Society of Korea
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• v.41 no.3
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• pp.326-334
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• 2022

In this paper, we propose speech enhancement algorithm as a pre-processing for robust speech recognition in noisy environments. Auxiliary-function-based Independent Vector Analysis (AuxIVA) is performed with weighted covariance matrix using time-varying variances with scaling factor from target masks representing time-frequency contributions of target speech. The mask estimates can be obtained using Neural Network (NN) pre-trained for speech extraction or diffuseness using Coherence-to-Diffuse power Ratio (CDR) to find the direct sounds component of a target speech. In addition, outputs for omni-directional noise are closely chained by sharing the time-varying variances similarly to independent subspace analysis or IVA. The speech extraction method based on AuxIVA is also performed in Independent Low-Rank Matrix Analysis (ILRMA) framework by extending the Non-negative Matrix Factorization (NMF) for noise outputs to Non-negative Tensor Factorization (NTF) to maintain the inter-channel dependency in noise output channels. Experimental results on the CHiME-4 datasets demonstrate the effectiveness of the presented algorithms.

• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.1-12
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• 2022

Traditional methods of measuring corneal ulcers were difficult to present objective basis for diagnosis because of the subjective judgment of the medical staff through photographs taken with special equipment. In this paper, we propose a method to detect the ulcer area on a pixel basis in corneal ulcer images using a semantic segmentation model. In order to solve this problem, we performed the experiment to detect the ulcer area based on the DeepLab model which has the highest performance in semantic segmentation model. For the experiment, the training and test data were selected and the backbone network of DeepLab model which set as Xception and ResNet, respectively were evaluated and compared the performances. We used Dice similarity coefficient and IoU value as an indicator to evaluate the performances. Experimental results show that when 'crop & resized' images are added to the dataset, it segment the ulcer area with an average accuracy about 93% of Dice similarity coefficient on the DeepLab model with ResNet101 as the backbone network. This study shows that the semantic segmentation model used for object detection also has an ability to make significant results when classifying objects with irregular shapes such as corneal ulcers. Ultimately, we will perform the extension of datasets and experiment with adaptive learning methods through future studies so that they can be implemented in real medical diagnosis environment.

• Journal of the Society of Disaster Information
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• v.19 no.1
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• pp.117-127
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• 2023

Purpose: The number of Cold Storages at home and abroad is on the rise, fires in large Cold Storages have recently occurred. As fires continue to occur and property damage is on the rise every year, the importance of preventing fires in large Cold Storage is growing. Method: Real Cold Storages were investigated on-site and fire cases were analyzed to derive and analyze fire risk, and the ORS, which is emerging as an adaptive fire prevention technology of Cold Storage, was investigated through FDS. Result: oxygen concentration 21, 15.7% and 17.7, 16.7% were analyzed through FDS, and flashover was reached within 3~4 minutes from 21, 17.7, 16.7%, but if oxygen concentration was lowered to 15.7%, it didn't ignite for 13 minutes. Conclusion: This study understood the concept and general part of the ORS, modeled the freezer through FDS, and analyzed the oxygen concentration to analyze the fire protection adaptability of the ORS. In the future, it is expected that large-scale empirical experiments and related regulations will be prepared to provide solutions for fire prevention in Cold Storages in blind spots of fire.

• Journal of Industrial Convergence
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• v.21 no.2
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• pp.125-131
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• 2023

In this paper, research was conducted to solve the problem of reducing the dimming level and flicker that occurs in the visible light communication system. Visible light communication is a convergence technology that provides both communication and lighting, and must satisfy not only communication performance but also lighting performance. However, since the existing data transmission method transmits without considering the transmission data sequence, it reduces the dimming level and causes a flicker phenomenon. To solve this problem, in this paper, the Dimming Improvement and Flicker Reduction Mapping technique was studied. Existing systems simply transmitted data of '0' and '1', but in this system, original data transmission channels and DIFR (Dimming Improvement and Flicker Reduction) transmission channels are assigned to RGB channels. Original data is allocated to the R channel and original data or inverse original data is allocated to the DIFR-G channel, and the DIFR-B channel maintains the maximum dimming level by transmitting through the logical operation of the R channel and the G channel. At the same time, the flicker phenomenon is prevented by preventing continuous occurrence of 'OFF' patterns. Through this, we proposed an adaptive data allocation algorithm that can faithfully play a role as a light as well as a communication function.

• Journal of the Society of Disaster Information
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• v.19 no.3
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• pp.608-623
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• 2023

Purpose: Recently, the number of logistics warehouses has been on the rise. In addition, as the number of such logistics warehouses increases, number of fire accidents also increases every year, increasing the importance of preventing fires in large logistics warehouses. Method: investigated aspirating smoke detectors that are emerging as adaptive fire detectors in logistics warehouses. Then, through fire simulation (FDS), logistics warehouse modeling was conducted to compare and analyze the detection speed of general smoke detectors and aspirating smoke detectors according to four stages of fire growth and three locations of fire in the logistics warehouse. Result: Growth speed in Slow-class fires and Mediumclass fires, the detection speed of aspirating smoke detectors was faster regardless of the location of the fire. However, in Fast-class fires and Ultra-Fast-class fires, it was confirmed that the detection speed of general smoke detectors was faster depending on the location of the fire. Conclusion: It was confirmed that the detection performance of the aspirating smoke detector decreased as the fire growth speed increased and the location of the fire occurred further than the receiver of the aspirating smoke detector. Therefore, even if an aspirating smoke detector is installed in a warehouse that stores combustibles with high fire growth rates, it is judged that an additional smoke detector is attached far away from the receiver of the general smoke detector to increase fire safety.

• Journal of the Korea Society for Simulation
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• v.19 no.2
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• pp.73-80
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• 2010

A wireless sensor network which is deployed in hostile environment can be easily compromised by attackers. The selective forwarding attack can jam the packet or drop a sensitive packet such as the movement of the enemy on data flow path through the compromised node. Xiao, Yu and Gao proposed the checkpoint-based multi-hop acknowledgement scheme(CHEMAS). In CHEMAS, each path node enable to be the checkpoint node according to the pre-defined probability and then can detect the area where the selective forwarding attacks is generated through the checkpoint nodes. In this scheme, the number of hops is very important because this parameter may trade off between energy conservation and detection capacity. In this paper, we used the fuzzy rule system to determine adaptive threshold value which is the number of hops for the ACK packets. In every period, the base station determines threshold value while using fuzzy logic. The energy level, the number of compromised node, and the distance to each node from base station are used to determine threshold value in fuzzy logic.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.3
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• pp.383-391
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• 2017

In image processing, image segmentation has been studied by various methods in a long time. Image segmentation is the process of partitioning a digital image into multiple objects and face detection is a typical image segmentation field being used in a variety of applications that identifies human faces in digital images. In this paper, we propose a method for extracting the contours of faces included in images. Using the Viola-Jones algorithm, to do this, we detect the approximate locations of faces from images. But, the Viola-Jones algorithm could detected the approximate location of face not the correct position. In order to extract a more accurate face region from image, we use skin color in this paper. In details, face region would be extracted using the analysis of horizontal and vertical histograms on the skin area. Finally, the face contour is extracted using snake algorithm for the extracted face area. In this paperr, a modified snake energy function is proposed for face contour extraction based snake algorithm proposed by Williams et al.[7]

• Tunnel and Underground Space
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• v.33 no.5
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• pp.312-338
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• 2023

The underground disposal facility for spent nuclear fuel demands a specialized design, distinct from conventional practices, to ensure long-term thermal, mechanical, and hydraulic integrity, preventing the release of radioactive isotopes from high-temperature spent nuclear fuel. SKB has established design criteria for such facilities and executed practical design implementations for Forsmark. Moreover, in response to subsurface uncertainty, SKB has proposed an empirical approach involving monitoring and adaptive design modifications, alongside stepwise development. SKB has further introduced a unique support system, categorizing ground types and behaviors and aligning them with corresponding support types to confirm safety through comparative analyses against existing systems. POSIVA has pursued a comparable approach, developing a support system for Onkalo while accounting for distinct geological characteristics compared to Forsmark. This demonstrates the potential for domestic implementation of spent nuclear fuel disposal facility designs and the establishment of a support system adapted to national attributes.

• The Journal of the Acoustical Society of Korea
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• v.29 no.7
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• pp.458-467
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• 2010

In this paper, a new audio reproduction system was developed in which the cross-talk signals would be reasonably cancelled at an arbitrary listener position. To adaptively remove the cross-talk signals according to the listener's position, a method of tracking the listener position was employed. This was achieved using the two microphones, where the listener direction was estimated using the time-delay between the two signals from the two microphones, respectively. Moreover, room reverberation effects were taken into consideration where linear prediction analysis was involved. To remove the cross-talk signals at the left-and right-ears, the paths between the sources and the ears were represented using the KEMAR head-related transfer functions (HRTFs) which were measured from the artificial dummy head. To evaluate the usefulness of the proposed listener tracking system, the performance of cross-talk cancellation was evaluated at the estimated listener positions. The performance was evaluated in terms of the channel separation ration (CSR), a -10 dB of CSR was experimentally achieved although the listener positions were more or less deviated. A real-time system was implemented using a floating-point digital signal processor (DSP). It was confirmed that the average errors of the listener direction was 5 degree and the subjects indicated that 80 % of the stimuli was perceived as the correct directions.