• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.271-274
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• 2014

This paper proposes high-performance SAO(Sample Adaptive Offset) in HEVC(High Efficiency Video Coding) encoder for Ultra HD video processing in real time. SAO is a newly adopted technique belonging to the in-loop filter in HEVC. The proposed SAO encoder hardware architecture uses three-layered buffers to minimize memory access time and to simplify pixel processing and also uses only adder, subtractor, shift register and feed-back comparator to reduce area. Furthermore, the proposed architecture consists of pipelined pixel classification and applying SAO parameters, and also classifies four consecutive pixels into EO and BO concurrently. These result in the reduction of processing time and computation. The proposed SAO encoder architecture is designed by Verilog HDL, and implemented by 180k logic gates in TSMC $0.18{\mu}m$ process. At 110MHz, the proposed SAO encoder can support 4K Ultra HD video encoding at 30fps in real time.

• Journal of the Korean earth science society
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• v.40 no.3
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• pp.272-282
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• 2019

Although the knowledge of current seismicity is a critical information for making and implementing effective earthquake-related policy, the detailed seismicity information of the metropolitan areas with high-population density has been largely underestimated due to the high-level of cultural noise and small earthquake magnitude. This study presents 12 earthquakes including 2 earthquakes previously known and 10 additional earthquakes occurred from 2010 to 2017 in Busan, but they were unreported by the Korea Meteorological Administration. Matched filter technique is used to detect micro-earthquakes. Although the epicenters of micro-earthquakes though present a distinguished linearity, a correlation with faults in the area is unknown. A repeated micro-seismicity suggests that there are subsurface structures responsible for observed events. If large earthquakes occur along the fault in Busan, they may cause catastrophic natural disasters. Given the fact that the recent earthquakes did not accompany any surface signatures, it is highly recommended that the current micro-seismicity be investigated, and updated seismicity information be incorporated into establishing active fault maps in Korea.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.5
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• pp.193-204
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• 2019

The explosion of data due to the improvement of sensor technology and computing performance has become the basis for analyzing the situation in the industrial fields, and various attempts to detect events based on such data are increasing recently. In particular, sound signals collected from sensors are used as important information to classify events in various application fields as an advantage of efficiently collecting field information at a relatively low cost. However, the performance of sound-event classification in the field cannot be guaranteed if noise can not be removed. That is, in order to implement a system that can be practically applied, robust performance should be guaranteed even in various noise conditions. In this study, we propose a system that can classify the sound event after generating the enhanced sound signal based on the deep learning algorithm. Especially, to remove noise from the sound signal itself, the enhanced sound data against the noise is generated using SEGAN applied to the GAN with a VAE technique. Then, an end-to-end based sound-event classification system is designed to classify the sound events using the enhanced sound signal as input data of CNN structure without a data conversion process. The performance of the proposed method was verified experimentally using sound data obtained from the industrial field, and the f1 score of 99.29% (railway industry) and 97.80% (livestock industry) was confirmed.

• Journal of Korean Society for Quality Management
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• v.46 no.4
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• pp.843-862
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• 2018

Purpose: The purpose of this study was to develop quality innovation techniques specialized for the small and medium-sized businesses. which account for the majority of Korean companies, were having a hard time utilizing the widely recognized quality innovation techniques due to resource constraints. Methods: First, we do review the existing Single PPM and 6 Sigma. And investigate the utilization of these methods including Toyota Production System. Second, we devised a four-step problem-solving methodology based on recent trends in quality innovation such as Simple, Speedy, and Smart. Third, we do survey on frequently used tools for quality innovation. Many opinion leaders including quality consultants and professors answered and gave us valuable comments about our selected quality tools. Finally, we do specify and map tools to each step of PASS. Results: In 2017, 167 companies participated in the quality innovation support business for small businesses according to the Korea Chamber of Commerce & Industry. We conducted performance checks on 167 companies that had completed the "PASS" projects. For the purpose of evaluating improvement performance, the survey was carried out using a structured questionnaire during the field visit of these companies mentioned above. For the reference, 165 out of 167 companies (98.8 % response rate) responded to the questionnaire and conducted performance analysis based on it. According to the survey, 97.6 percent of the respondents were very satisfied with their overall satisfaction with the quality innovation support projects for small and medium sized enterprises in 2017. Also, 93.3 % of the respondents were satisfied with the results of level of the target achievement. As a result, 160 companies (97.0 % of the participating companies) hope to partic ipate in the quality improvement project using "PASS" once again. Conclusion: In this paper, we introduce the new quality innovation methodology, which is named as 'PASS', It could support the long-range business plan of the small and medium-sized businesses to achieve total customer satisfaction resulting in increased market share and improved profit margin. The most small companies can use this "PASS" technique more easily, quickly and most efficiently than their existing known quality innovation techniques such as Six Sigma and Single PPM, etc.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.161-168
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• 2019

Recently, video equipments such as CCTV, which is spreading rapidly, is being used as a means to monitor and cope with abnormal situations in almost governments, companies, and households. However, in most cases, since recognizing the abnormal situation is carried out by the monitoring person, the immediate response is difficult and is used only for post-analysis. In this paper, we present the results of the development of video surveillance system that automatically recognizing the abnormal situations and sending such events to the smartphone immediately using the latest deep learning technology. The proposed system extracts skeletons from the human objects in real time using Openpose library and then recognizes the human behaviors automatically using deep learning technology. To this end, we reconstruct Openpose library, which developed in the Caffe framework, on Darknet framework to improve real-time processing. We also verified the performance improvement through experiments. The system to be introduced in this paper has accurate and fast behavioral recognition performance and scalability, so it is expected that it can be used for video surveillance systems for various applications.

• Journal of the Korean Society of International Agriculture
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• v.30 no.4
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• pp.339-346
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• 2018

Cyanazine is a member of the triazine family of herbicides. Cyanazine is used as a pre- and post-emergence herbicide for the control of annual grasses and broadleaf weeds. This experiment was conducted to establish a determination method for cyanazine, as domestic unregistered pesticide, residue in major agricultural commodities using HPLC-DAD/MS. Cyanazine was extracted with acetone from representative samples of five raw products which comprised apple, green pepper, Kimchi cabbage, hulled rice and soybean. The extract was diluted with saline water and partitioned to dichloromethane for remove polar extractive in the aqueous phase. For the hulled rice and soybean samples, n-hexane/acetonitrile partition was additionally employed to remove non-polar lipids. The extract was finally purified by optimized florisil column chromatography. On a $C_{18}$ column in HPLC, cyanazine was successfully separated from co-extractives of sample, and sensitively quantitated by diode array detection at 220 nm. Accuracy and precision of the proposed method was validated by the recovery experiment on every major agricultural commodity samples fortified with cyanazine at 3 concentration levels per agricultural commodity in each triplication. Mean recoveries were ranged from 83.6 to 93.3% in five major representative agricultural commodities. The coefficients of variation were all less than 10%, irrespective of sample types and fortification levels. Limit of quantitation(LOQ) of cyanazine was 0.02 mg/kg as verified by the recovery experiment. A confirmatory method using LC/MS with selected-ion monitoring(SIM) technique was also provided to clearly identify the suspected residue.

• Journal of the Korea Institute of Building Construction
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• v.21 no.2
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• pp.121-128
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• 2021

Due to the increase of size and complexity of construction project, the frequency of serious accidents in construction industry has been increased. Especially, the proportion of accidents in formwork of building construction site is very high, and many previous studies have been conducted to preventing them in the viewpoint of the diverse approaches. However, their effectiveness on accidents prevention was poor, and as a result, it is limited to consider the potential risks because many workers and managers tend not to be concerned with unsafe factors in formwork. Therefore, in this study, a realistic and proactive way for analyzing these potential risks was proposed in the manner of quantitatively assessing the potentials resulted from the unsafe factors in formwork. To verify the applicability of the proposed methodology, group survey was carried out, and the results were compared with those of the traditional importance-performance analysis(hereafter IPA) technique. Through the use of the proposed methodology, unsafe factors that were not found in the IPA but have potential risk were identified. Eventually, this study is expected to contribute to the proactive prevention of construction serious disaster accidents in formwork by enabling a more efficient management.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.8
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• pp.287-300
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• 2021

Collaborative Cyber-Physical Systems (CCPS) are those systems that contain tightly coupled physical and cyber components, massively interconnected subsystems, and collaborate to achieve a common goal. The safety of a single Cyber-Physical System (CPS) can be achieved by following the safety standards such as ISO 26262 and IEC 61508 or by applying hazard analysis techniques. However, due to the complex, highly interconnected, heterogeneous, and collaborative nature of CCPS, a fault in one CPS's components can trigger many other faults in other collaborating CPSs. Therefore, a safety assurance technique based on fault criticality analysis would require to ensure safety in CCPS. This paper presents a Fault Criticality Matrix (FCM) implemented in our tool called CPSTracer, which contains several data such as identified fault, fault criticality, safety guard, etc. The proposed FCM is based on composite hazard analysis and content-based relationships among the hazard analysis artifacts, and ensures that the safety guard controls the identified faults at design time; thus, we can effectively manage and control the fault at the design phase to ensure the safe development of CPSs. To justify our approach, we introduce a case study on the Platooning system (a collaborative CPS). We perform the criticality analysis of the Platooning system using FCM in our developed tool. After the detailed fault criticality analysis, we investigate the results to check the appropriateness and effectiveness with two research questions. Also, by performing simulation for the Platooning, we showed that the rate of collision of the Platooning system without using FCM was quite high as compared to the rate of collisions of the system after analyzing the fault criticality using FCM.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.4
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• pp.269-274
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• 2021

In secret communication, steganography is the sending and receiving of secret messages without being recognized by a third party. In the spatial domain method bitwise information is inserted into the virtual bit plane of the decomposed pixel values of the image. That is, the bitwise secret message is sequentially inserted into the least significant bit(LSB) of the image, which is a cover medium. In terms of application, the LSB is simple, but has a drawback that can be easily detected by a third party. If the upper bit plane is used to increase security, the image quality may deteriorate. In this paper, I present a method for concealing Hangul secret messages in image steganography based on the lo-th bit plane and the decomposition of modified pixel intensity values. After decomposing the Hangeul message to be hidden into choseong, jungseong and jongseong, then a shuffling process is applied to increase confidentiality and robustness. PSNR was used to confirm the efficiency of the proposed method. It was confirmed that the proposed technique has a smaller effect in terms of image quality than the method applying BCD and Fibonacci when inserting a secret message in the upper bit plane. When compared with the reference value, it was confirmed that the PSNR value of the proposed method was appropriate.

• Journal of Internet Computing and Services
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• v.20 no.5
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• pp.87-94
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• 2019

In this paper, the method of analyzing the unformatted data of consumers accumulated on social networks in the era of the Fourth Industrial Revolution by utilizing data from the service design and social psychology aspects was proposed. First, the fandom phenomenon, which shows subjective and collective behavior in a space on a social network rather than physical space, was defined from a data service perspective. The fandom model has been transformed into a collective level of customer Persona that has been analyzed at a personal level in traditional service design, and social network analysis that analyzes consumers' big data has been presented as an efficient way to pattern and visually analyze it. Consumer data collected through social leasing were pre-processed by column based on correlation, stability, missing, and ID-ness. Based on the above data, the company's brand strategy was divided into active and passive interventions and the effect of this strategic attitude on the growth direction of the consumer's fandom community was analyzed. To this end, the fandom model of consumers was proposed by dividing it into four strategies that the brand strategy had: stand-alone, decentralized, integrated and centralized, and the fandom shape of consumers was proposed as a growth model analysis technique that analyzes changes over time.