• Journal of Veterinary Science
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• v.21 no.3
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• pp.21.1-21.14
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• 2020

Background: Physical exercise is known to cause significant joint changes. Thus, monitoring joint behavior of athletic horses is essential in early disorders recognition, allowing the proper management. Objectives: The aims of this study were to determine the morphological patterns, physical examination characteristics and ultrasound findings of show jumping horses in training and to establish a score-based examination model for physical and ultrasound follow-ups of metacarpophalangeal joint changes in these animals. Methods: A total of 52 metacarpophalangeal joints from 26 horses who were initially in the taming stage were evaluated, and the horses' athletic progression was monitored. The horses were evaluated by a physical examination and by B-mode and Doppler-mode ultrasound examinations, starting at time zero (T0), which occurred concomitantly with the beginning of training, and every 3 months thereafter for a follow-up period of 18 months. Results: The standardized examination model revealed an increase in the maximum joint flexion angles and higher scores on the physical and ultrasound examinations after scoring was performed by predefined assessment tools, especially between 3 and 6 months of evaluation, which was immediately after the horses started more intense training. The lameness score and the ultrasound examination score were slightly higher at the end of the study. Conclusions: The observed results were probably caused by the implementation of a training regimen and joint adaptation to physical conditioning. The joints most likely undergo a pre-osteoarthritic period due to work overload, which can manifest in a consistent or adaptive manner, as observed during this study. Thus, continuous monitoring of young athlete horses by physical and ultrasound examinations that can be scored is essential.

• Smart Structures and Systems
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• v.30 no.6
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• pp.661-671
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• 2022

Stayed cables are the key components for transmitting loads in cable-stayed bridges. Therefore, it is very important to evaluate the cable force condition to ensure bridge safety. An online condition assessment and anomaly localization method is proposed for cables based on the spatiotemporal correlation of grouped cable forces. First, an anomaly sensitive feature index is obtained based on the distribution characteristics of grouped cable forces. Second, an adaptive anomaly detection method based on the k-nearest neighbor rule is used to perform dissimilarity measurements on the extracted feature index, and such a method can effectively remove the interference of environment factors and vehicle loads on online condition assessment of the grouped cable forces. Furthermore, an online anomaly isolation and localization method for stay cables is established, and the complete decomposition contributions method is used to decompose the feature matrix of the grouped cable forces and build an anomaly isolation index. Finally, case studies were carried out to validate the proposed method using an in-service cable-stayed bridge equipped with a structural health monitoring system. The results show that the proposed approach is sensitive to the abnormal distribution of grouped cable forces and is robust to the influence of interference factors. In addition, the proposed approach can also localize the cables with abnormal cable forces online, which can be successfully applied to the field monitoring of cables for cable-stayed bridges.

• Korean Journal of Culture and Social Issue
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• v.17 no.4
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• pp.381-393
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• 2011

Eco driving is a strategy to reduce energy consumption and greenhouse gas emissions from motor vehicle. However, it has not received much attention until recently. Psychological studies on this issue have been limited and the majority of existing studies have primarily been based on engineering and educational approaches. This study examined the effects of a self-management technique on two driving behaviors: speeding and putting the gears in neutral while waiting at the signal. The self-management technique consisted of three behavior interventions: goal-setting, self-monitoring, and reward. Three drivers participated in this study. An AB multiple baseline design across participants was adopted. Results showed that the self-management technique was effective in increasing both driving behaviors. Implications of the present findings and suggestions for future research were discussed.

• International Journal of Computer Science & Network Security
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• v.23 no.1
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• pp.147-152
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• 2023

Mostly in motor fault detection the instantaneous values 3 axis vibration and 3phase current in time domain are acquired and converted to frequency domain. Vibrations are more useful in diagnosing the mechanical faults and motor current has remained more useful in electrical fault diagnosis. With having some experience and knowledge on the behavior of acquired data the electrical and mechanical faults are diagnosed through signal processing techniques or combine machine learning and signal processing techniques. In this paper, a single-layer LSTM based condition monitoring system is proposed in which the instantaneous values of three phased motor current are firstly acquired in simulated motor in in health and supply imbalance conditions in each of three stator currents. The acquired three phase current in time domain is then used to train a LSTM network, which can identify the type of fault in electrical supply of motor and phase in which the fault has occurred. Experimental results shows that the proposed single layer LSTM algorithm can identify the electrical supply faults and phase of fault with an average accuracy of 88% based on the three phase stator current as raw data without any processing or feature extraction.

• Computers and Concrete
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• v.31 no.5
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• pp.405-417
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• 2023

The submerged floating tunnel (SFT) is tethered by mooring lines anchored to the seabed, therefore, the structural integrity of the anchor should be sensitively managed. Despite their importance, reaction forces cannot be simply measured by attaching sensors or load cells because of the structural and environmental characteristics of the submerged structure. Therefore, we propose an effective method for estimating the reaction forces at the seabed anchor of a submerged floating tunnel using a structural pattern model. First, a structural pattern model is established to use the correlation between tunnel motion and anchor reactions via a deep learning algorithm. Once the pattern model is established, it is directly used to estimate the reaction forces by inputting the tunnel motion data, which can be directly measured inside the tunnel. Because the sequential characteristics of responses in the time domain should be considered, the long short-term memory (LSTM) algorithm is mainly used to recognize structural behavioral patterns. Using hydrodynamics-based simulations, big data on the structural behavior of the SFT under various waves were generated, and the prepared datasets were used to validate the proposed method. The simulation-based validation results clearly show that the proposed method can precisely estimate time-series reactions using only acceleration data. In addition to real-time structural health monitoring, the proposed method can be useful for forensics when an unexpected accident or failure is related to the seabed anchors of the SFT.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.339-339
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• 2020

도시화로 인한 불투수면적의 증가와 기후 변화로 인한 강우패턴의 변화 자연적 물순환 체계에 악영향을 미치며. 이를 해결하기 위하여 국내에서는 도시 내 빗물관리 및 비점오염원 저감이 가능한 저영향개발(Low Impact Development, LID)를 적용하고 있다. 건기시 도로, 주차장등 차량통행 및 유동인구가 많은 지역에서는 입자상 물질들이 많이 발생되어 노면에 축적되어 있다가 강우시 강우유출수를 통해 시설로 유입된다. 이로 인해 시설 내 오염물질 및 퇴적물이 축적되어 여재 공극막힘현상 및 침투율저하의 문제가 발생되어 시설 내 효율이 감소된다. 따라서, 레인가든의 장기 모니터링을 통해 시설 내 유입되는 오염물질의 성상 분석 및 시설 내부의 퇴적물 분석을 통해 LID시설 운영의 효율성 평가를 수행하였다. 모니터링은 강우시 모니터링과 건기시 집수구역, 침강지, 시설 상부, 중부, 하부 등 총 5곳에서 채취하여 분석을 수행하였다. 모니터링은 평균 선행건기 일수는 5.46±4.7 days, 평균 강우량은 14.31±11.4 mm, 평균 강우강도는 5.33±6.7 mm/hr의 강우사상에서 모니터링을 수행하였다. 시설 내 평균 유입수농도는 TSS 98.0 ± 32.7 mg / L, COD 133.6 ± 6.3 mg / L, TN 5.77 ± 4.05 mg, TP 0.54 ± 0.03 mg / L으로 분석되었다. 유입부 내 퇴적물 종류는 Sandy Clay Loam으로 나타났으며, Cr 0.36mg / kg, Cu 5.17 mg / kg and Pb 6.04 mg / kg으로 중금속의 함유량이 높은것으로 분석되었다. 퇴적물은 침강지 및 시설 유입부에서의 입자크기는 49-113㎛ 약 60%의 퇴적물이 축적되어 제거되는 것으로 나타났다. 시설 내 침강지에서 50㎛ 이상의 입자들이 여과, 흡착 및 침전으로 인하여 40% 이상의 입자들이 제거되는 것으로 분석되었으며, 50㎛ 미만의 입자들은 시설 내 중간부, 유출부에서 제거되는 것으로 분석되었다. 침강지에서 유입수 대부분의 입자상물질들이 흡착 및 여과로 인한 제거가 이루어지기에 침강지 여재부는 넓은 표면적, 우수한 흡착능 및 여과율을 고려하여 선정하영 하며, 잦은 교체를 위하여 중량성이 낮은 우드칩 등이 적당한 것으로 사료된다.

• Journal of Information Science Theory and Practice
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• v.10 no.spc
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• pp.143-153
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• 2022

With the development of networks and the increase in the number of network devices, the number of cyber attacks targeting them is also increasing. Since these cyber-attacks aim to steal important information and destroy systems, it is necessary to minimize social and economic damage through early detection and rapid response. Many studies using machine learning (ML) and artificial intelligence (AI) have been conducted, among which payload learning is one of the most intuitive and effective methods to detect malicious behavior. In this study, we propose a preprocessing method to maximize the performance of the model when learning the payload in term units. The proposed method constructs a high-quality learning data set by eliminating unnecessary noise (stopwords) and preserving important features in consideration of the machine language and natural language characteristics of the packet payload. Our method consists of three steps: Preserving significant special characters, Generating a stopword list, and Class label refinement. By processing packets of various and complex structures based on these three processes, it is possible to make high-quality training data that can be helpful to build high-performance ML/AI models for security monitoring. We prove the effectiveness of the proposed method by comparing the performance of the AI model to which the proposed method is applied and not. Forthermore, by evaluating the performance of the AI model applied proposed method in the real-world Security Operating Center (SOC) environment with live network traffic, we demonstrate the applicability of the our method to the real environment.

• Korean Journal of Environmental Biology
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• v.26 no.4
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• pp.330-342
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• 2008

A comprehensive quality survey for PCDDs/PCDFs and coplanar PCBs as well as heavy metals (Cu, Zn, Cd and Pb) in sediments has been investigated in August 2006, Korea. Monitoring was undertaken at five streams representing different surrounding environments throughout Juwang and Gapyeong streams (reference sites), Jungrang stream (dense population site), Ansan stream (mixed small population and industrial site), and Siheung stream (heavy industrial site). The levels of heavy metal in samples were found to be significantly higher in sediment from Siheung stream compared to those of other stream sites. The heavy metal concentrations (dry weight basis) in sediment from Siheung stream were as follows; Cd (3.7 ${\mu}g$/g), Pb (1,295 ${\mu}g$/g), Cu (713.4 ${\mu}g$/g) and Zn (358.1 ${\mu}g$/g). Among 12 coplanar PCBs and 17 PCDDs/PCDFs selected as target compounds in this study, PCB (IUPAC no. 118) and OCDD were the most abundant congeners found in all sediment samples, followed by 1,2,3,4,6,7,8-HpCDD, OCDF and 1,2,3,4,6,7,8HpCDF as well as PCB (IUPAC no. 105). These results were shown to be in the same trend as the sediment samples of other countries. The levels of PCDDs/PCDFs/coplanar PCBs in sediment samples were expressed as concentrations and WHO- TEQ values. The PCDDs/PCDFs/coplanar PCBs concentrations and their WHO-TEQ values in sediment from Siheung stream were remarkably high. The levels detected were 788.16 pg/g and 36.080 pg WHO-TEQ/g dry weight for PCDDs/ PCDFs and 314 pg/g and 0.4189 pg WHO-TEQ/g dry weight for coplanar PCBs, respectively, beyond the safety level of sediment value 20 pg WHO-TEQ/g. Sediment samples of the five streams were also monitored by sensitive biomarkers using insect immune responses: hemocyte-spreading behavior and immune-associated enzyme activities of phospholipase A$_2$ (PLA$_2$) and phenoloxidase. Organic extracts of Siheung and Jungrang sediments significantly interfered with the hemocytespreading behavior, whereas those of Ansan, Gapyeong, and Juwang did not. These organic extracts did not inhibit the PLA$_2$ and phenoloxidase activities. However, phenoloxidase was highly susceptible to exposure to aqueous extracts in all site sediments. In comparison, PLA$_2$ activities of the hemocytes were significantly inhibited only by aqueous extracts of Siheung, Jungrang, and Gapyeong sediments, but not by those of Ansan and Juwang. Despite some disparity between bioand chemical monitoring results, the biomarkers can be recommended as a device warning the contamination of biohazard environmental chemicals because of a fast and inexpensive detection method.

• Korean journal of applied entomology
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• v.52 no.4
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• pp.335-340
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• 2013

As the market of educational pet insects is expanding, understanding the consumer needs became more crucial. To achieve the ideal analysis on the market, this research monitored the behavior of consumers. The posting on the blogs of consumers, who have visited insect museums and farms, or have bought insects were collected as data. Moreover, the informational contents, photographs and texts, were analyzed. The results showed that the family-unit visitors with elementary school lower graders were the main type of visitors for their children's education. The visiting areas were concentrated in Seoul and the Metropolitans of Gyeonggi province, and the visits were mostly occurred during their children's vacation period. The analysis of posted photographs showed the visitors' high interest in the hands-on program. According to the texts on visitors' blogs, especially, the largest number of visitors satisfied with the variety of program. It implies the necessity of development in diverse and differentiated hands-on program. Otherwise, the programs available to connect insects to other animals and plants should be introduced to reduce aversion against insects, which was reported as the strongest dissatisfaction. In conclusion, diversification on insect species and development in systematized hands-on program seem to be required for the continuous growth of educational pet insects market.

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.6
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• pp.559-575
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• 2021

Due to the increase in ground excavation work, the possibility of ground subsidence accidents is increasing. And it is very difficult to prevent these risk fundamentally through institutional reinforcement such as the special law for underground safety management. As for the various cases of urban ground excavation practice, the ground subsidence behavior characteristics which is predicted using various information before excavation showed a considerable difference that could not be ignored compared to the results real construction data. Changes in site conditions such as seasonal differences in design and construction period, changes in construction methods depending on the site conditions and long-term construction suspension due to various reasons could be considered as the main causes. As the countermeasures, the safety management system through various construction information is introduced, but there is still no suitable system which can predict the effect of excavation and risk assessment. In this study, a web-based system was developed in order to predict the degree of impact on the ground subsidence and surrounding structures in advance before ground excavation and evaluate the risk in the design and construction of urban ground excavation projects. A system was built using time series analysis technique that can predict the current and future behavior characteristics such as ground water level and settlement based on past field construction records with field monitoring data. It was presented as a geotechnical data visualization (GDV) technology for risk reduction and disaster management based on web-based system, Using this newly developed web-based assessment system, it is possible to predict ground excavation impact prediction and risk assessment.