• Korean Journal of Construction Engineering and Management
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• v.23 no.1
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• pp.73-82
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• 2022

Waste paint, one of the specified wastes in Korea, is currently treated entirely by incineration treatment method, and is hardly recycled compared to other wastes. Incineration treatment method also causes environmental problems such as air pollution. Thus, this study breaks away from the existing incineration treatment method of waste paint and switch to a method of pretreatment operation through evaporation, condensation, and thermal decomposition by temperature control. and then proposes a sustainable waste paint treatment process that can be recycled as an alternative energy heat source. If a new method of disposing of waste paint and technology for recycling are developed and disseminated, it is expected that the effect will be large from an economic and environmental point of view.

• Journal of Advanced Navigation Technology
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• v.26 no.4
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• pp.219-225
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• 2022

In this paper, we propose a CAC exploring a RA based dynamic spectrum hole grouping for secondary users' QoS enhancement in multi-classes cognitive radio networks. The RA based dynamic spectrum hole grouping uses SU multi-classes overlaying spectrum structure suggested here. Multiclass SUs are divided into real and non real, and real SUs have a priority for resource utilization against non real. The amount of resource required by real SUs is supported by Wiener prediction and the dynamic spectrum hole grouping, and that required by non real SU is supported by the remained available amount without prediction. In the simulations, we compare the proposed CAC performances using the dynamic spectrum hole grouping in terms of SU connection's blocking(dropping) rate and resource utilization efficiency according to multi-classes traffic characteristics, and then we show the proposed CAC can guarantee the desired QoS of multi-classes secondary users.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.615-624
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• 2022

In this study, we assessed anti-oxidant activity, anti-microbial, inhibition of biofilm formation and inflammatory factors(nitric oxide, interleukin-6, interleukin-8) inhibitory effect of Perillae semen hydrothermal extract(PSW) and three kinds of Perillae semen supercritical fluid extract(PSSs) extracted by controlling temperature with no variation of pressure. Compared with PSW, PSSs had significantly lower minimal inhibitory concentrations(MICs) against Staphylococcus aureus(S. aureus) and the ability of PSSs to inhibit formation of biofilm was also superior. PSSs reduce the production of inflammatory mediator and inflammatory cytokines significantly compared to PSW. We suggest, therefore, Perillae semen supercritical fluid 45℃ extract which showed the best anti-microbial, inhibition of biofilm formation, and inhibition of inflammatory factors production among the supercritical fluid extracts could be used for protecting patients with atopic dermatitis from pruritus and transepidermal water loss as a functional ingredient from nature.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.863-867
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• 2021

In this paper, in order to hide the watermark in the LSB of the color image, a color image watermarking technique with high security is proposed by using the adjacent pixels of the image and the spatial encryption technique. According to the technique proposed in this paper, the quality of the stego-image generated by hiding the watermark in the LSB of the color image is so excellent that the difference from the original image cannot be recognized, and the original watermark can be extracted from the stego-image without loss. If the watermark is hidden in the image using the proposed technique, the security of the watermark is maintained very high because the watermark hidden in the stego-image is multi-encrypted. The proposed watermarking technique can be used in applications such as military and intellectual property protection that require high security.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.3
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• pp.413-420
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• 2023

For a long time, researchers have presented excellent results in the field of image retrieval due to many studies on CBIR. However, there is still a semantic gap between these search results for images and human perception. It is still a difficult problem to classify images with a level of human perception using a small number of images. Therefore, this paper proposes an image classification model using deep learning-based transfer learning to minimize the semantic gap between images of people and search systems in image retrieval. As a result of the experiment, the loss rate of the learning model was 0.2451% and the accuracy was 0.8922%. The implementation of the proposed image classification method was able to achieve the desired goal. And in deep learning, it was confirmed that the CNN's transfer learning model method was effective in creating an image database by adding new data.

• The Journal of the Acoustical Society of Korea
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• v.41 no.2
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• pp.218-226
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• 2022

The main characteristics of the underwater acoustic channel have varying multipath and fast fading. Especially, Frequency Shift Keying (FSK) signals with multiple frequency bands caused loss of information bits allocated on the specific frequencies due to selective fading phenomenon. Therefore, this paper proposes frequency gain control algorithm based on preamble error rates. The proposed algorithm estimates optimal gain value in the range of preamble error rate with less than 10 % for specific faded frequency. By employing turbo equalized FSK signals with rate of 1/3, the experiment was conducted on a lake in Munkyeong city with distance of 300 m to 500 m. The result confirms that packets are decoded successfully by applying proposed algorithm as increasing number of iterations.

• Annual Conference of KIPS
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• 2021.11a
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• pp.1188-1191
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• 2021

The function of the black box can be combined with a car to check the video through a cloud server, reduce the hassle of checking the video through a memory card, check the black box image in real time through a PC and smartphone, and check the user's Excel, brake operation status, and handle control record at the time of the accident. In addition, the goal was to accurately identify vehicle accidents and simplify accident handling through artificial intelligence object recognition of black box images using cloud services. Measures can be prepared to preserve images even if the black box itself loses, such as fire, flooding, or damage that occurs in an accident. It has been confirmed that the exact situation before and after the accident can be grasped immediately by providing object recognition and log recording functions under actual driving experimental conditions.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2019.11a
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• pp.264-264
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• 2019

The purpose of this paper is to establish development concepts for a novel collision avoidance system with preventing function of navigator's human error (Hu-CAS) in ship control behaviors. Hu-CAS consists of four modules: 1) collision risk assessment module to estimate collision priority between the ship and objects, 2) decision-making module to decide collision risk levels, 3) parameter estimation module needed in the ship control to avoid collisions and 4) control system to control the rudder angle and speed. Hu-CAS, proposed in this paper, can provide a novel system substitution current Autopilot and/or a CAS be teen manned vessel and Autonomous ship in a future.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.115-117
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• 2021

Currently, as IoT technology develops, monitoring systems are being used in various fields, and image processing is being used in various forms. Image data causes noise due to various causes during the transmission and reception process, and if it is not removed, loss of image information or error propagation occurs. Therefore, denoising images is essential. Typical methods of eliminating Salt and Pepper noise in images include AF, MF, and A-TMF. However, existing methods have the disadvantage of being somewhat inadequate in high-density noise. Therefore, in this paper, we propose an algorithm for determining noise for Salt and Pepper denoising and replacing the central pixel with an original pixel if it is non-noise, and processing the filtering mask by segmenting and averaging it in eight directions. We evaluate the performance by comparing and analyzing the proposed algorithms with existing methods.

• Journal of the Korea Society of Computer and Information
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• v.28 no.4
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• pp.13-20
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• 2023

In this paper, the actual data of VOC reduction facilities was analyzed through a model that detects and predicts data anomalies. Using the USAD model, which shows stable performance in the field of anomaly detection, anomalies in real-time data are detected and sensors that cause anomalies are searched. In addition, we propose a method of predicting and warning, when abnormalities that time will occur by predicting future outliers with an auto-regressive model. The experiment was conducted with the actual data of the VOC reduction facility, and the anomaly detection test results showed high detection rates with precision, recall, and F1-score of 98.54%, 89.08%, and 93.57%, respectively. As a result, averaging of the precision, recall, and F1-score for 8 sensors of detection rates were 99.64%, 99.37%, and 99.63%. In addition, the Hamming loss obtained to confirm the validity of the detection experiment for each sensor was 0.0058, showing stable performance. And the abnormal prediction test result showed stable performance with an average absolute error of 0.0902.