• Investigative Magnetic Resonance Imaging
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• v.25 no.2
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• pp.93-100
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• 2021

Purpose: (1) To evaluate the trabecular pattern at the femoral attachment of the posterior cruciate ligament (PCL) in patients with a PCL injury; (2) to analyze bone microarchitecture by applying gray level co-occurrence matrix (GLCM)-based texture analysis; and (3) to determine if there is a significant relationship between bone microarchitecture and posterior instability. Materials and Methods: The study included 96 patients with PCL tears. Trabecular patterns were evaluated on T2-weighted MRI qualitatively, and were evaluated by GLCM texture analysis quantitatively. The grades of posterior drawer test (PDT) and the degrees of posterior displacement on stress radiographs were recorded. The 96 patients were classified into two groups: acute and chronic injury. And 27 patients with no PCL injury were enrolled for control. Pearson's correlation coefficient and one-way ANOVA with Bonferroni test were conducted for statistical analyses. This protocol was approved by the Institutional Review Board. Results: A thick and anisotropic trabecular bone pattern was apparent in normal or acute injury (n = 57/61;93.4%), but was not prominent in chronic injury and posterior instability (n = 31/35;88.6%). Grades of PDT and degrees of posterior displacement on stress radiograph were not correlated with texture parameters. However, the texture analysis parameters of chronic injury were significantly different from those of acute injury and control groups (P < 0.05). Conclusion: The trabecular pattern and texture analysis parameters are useful in predicting posterior instability in patients with PCL injury. Evaluation of the bone microarchitecture resulting from altered biomechanics could advance the understanding of PCL function and improve the detection of PCL injury.

• Journal of the Korean Geotechnical Society
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• v.37 no.3
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• pp.5-17
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• 2021

This study aims to investigate the causes and countermeasures for the occurrence of tension cracks in the slope of the rock mass of heavy equipment for road construction. Electric resistivity survey was performed to investigate the expandable tensile crack range. As a result of examining the distribution of soft zones in the rock mass, a low specific resistance zone was found at the bottom of the access road where tensile cracks occurred. It was confirmed that a low resistivity zone was distributed near the top of the excavation slope. Therefore, reinforcements was performed by determining the location of the possible tensile crack as the top of the excavation slope. Two rows of reinforced piles and anchors were proposed as a reinforcement method, and the slope stability analysis showed that the allowable safety factor was satisfied after reinforcements.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.1113-1122
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• 2020

Recently, as violent crimes of crime without reason (Korea : Do not ask), women and the elderly are getting serious. In the existing system, many CCTVs are installed, but it is difficult to prevent crime due to only follow-up measures after a crime occurs. This device prevents crime through this device for incidents in shaded areas and closed spaces such as apartments and buildings. To do this, we research this technology to develop products and software. It sends an alarm signal using communication technology to a specific place where you want to receive an event of an alarm or a CCTV device operated using image analysis big data technology and convergence sensor technology for a specific target of the behavior expected to be a crime or movement. Develop the device. This development device researches and develops this device and supplies low-cost devices to consumers, which is used as a device that predicts the occurrence of crime in advance, processes it as an alarm signal in real time, and transmits it, and constitutes a standalone device and a server. Will provide the device to be connected.

• The Transactions of the Korean Institute of Power Electronics
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• v.26 no.4
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• pp.271-276
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• 2021

Arc fault detector based on multilevel DWT with analysis of high-frequency noise components over 100 kHz is proposed in this study to improve the performance in detecting serial arcs and distinguishing them from inverter noise in PV systems. PV inverters generally operate at a frequency range of 20-50 kHz for switching operation and maximum power tracking control, and the effect of these frequency components on the signal for arc detection leads to negative arc detection. High-speed ADC and multilevel DWT are used in this study to analyze frequency components above 100 kHz. Such high frequency components are less influenced by inverter noise and utilized to detect as well as separate DC series arc from inverter noise. Arc detectors identify the input current of PV inverters using a Rogowski coil. The sensed signal is filtered, amplified, and used in 800kSPS ADC and DWT analysis and arc occurrence determination in DSP. An arc detection simulation facility in UL1699B was constructed and AFD tests the proposed detector were conducted to verify the performance of arc detection and performance of distinction of the negative arc. The satisfactory performance of the arc detector meets the standard of arc detection and extinguishing time of UL1699B with an arc detection time of approximately 0.11 seconds.

• The Plant Pathology Journal
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• v.37 no.6
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• pp.662-672
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• 2021

Plant growth-promoting bacteria improve plant growth under abiotic stress conditions. However, their effects on microbial succession in the rhizosphere are poorly understood. In this study, the inoculants of Bacillus mesonae strain H20-5 were administered to tomato plants grown in soils with different salinity levels (EC of 2, 4, and 6 dS/m). The bacterial communities in the bulk and rhizosphere soils were examined 14 days after H20-5 treatment using Illumina MiSeq sequencing of the bacterial 16S rRNA gene. Although the abundance of H20-5 rapidly decreased in the bulk and rhizosphere soils, a shift in the bacterial community was observed following H20-5 treatment. The variation in bacterial communities due to H20-5 treatment was higher in the rhizosphere than in the bulk soils. Additionally, the bacterial species richness and diversity were greater in the H20-5 treated rhizosphere than in the control. The composition and structure of the bacterial communities varied with soil salinity levels, and those in the H20-5 treated rhizosphere soil were clustered. The members of Actinobacteria genera, including Kineosporia, Virgisporangium, Actinoplanes, Gaiella, Blastococcus, and Solirubrobacter, were enriched in the H20-5 treated rhizosphere soils. The microbial co-occurrence network of the bacterial community in the H20-5 treated rhizosphere soils had more modules and keystone taxa compared to the control. These findings revealed that the strain H20-5 induced systemic tolerance in tomato plants and influenced the diversity, composition, structure, and network of bacterial communities. The bacterial community in the H20-5 treated rhizosphere soils also appeared to be relatively stable to soil salinity changes.

• Explosives and Blasting
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• v.40 no.1
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• pp.1-16
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• 2022

In order to develop effective and safe blasting techniques or to introduce foreign advanced blasting techniques to domestic industry, the analysis of research trend in blasting field in the world is essential. In generally, such a research trend analysis was carried out for limited number of published papers. In this study, a bibliometric analysis was performed using VOSviewer for the overall papers published in international journals to figure out the variation of research trend in blasting area. From the keyword analysis, it was found that the number of published papers and the number of overall keywords was limited in the 2000s. Since 2010, the number of published papers was increased rapidly and the keywords were diversified with the introduction of artificial intelligence(AI). The keyword analysis for 2017~2021 showed that various hybrid AI techniques were actively applied in the evaluation of blasting effect.

• Journal of Korean Academy of Nursing
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• v.51 no.6
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• pp.720-731
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• 2021

Purpose: The purpose of this study was to identify the knowledge structure of health information (HI) for chronic obstructive pulmonary disease (COPD). Methods: Keywords or meaningful morphemes from HI presented on five health-related websites (HRWs) of one national HI institute and four hospitals, as well as HI needs among patients presented in nine literature, were reviewed, refined, and analyzed using text network analysis and their co-occurrence matrix was generated. Two networks of 61 and 35 keywords, respectively, were analyzed for degree, closeness, and betweenness centrality, as well as betweenness community analysis. Results: The most common keywords pertaining to HI on HRWs were lung, inhaler, smoking, dyspnea, and infection, focusing COPD treatment. In contrast, HI needs among patients were lung, medication, support, symptom, and smoking cessation, expanding to disease management. Two common sub-topic groups in HI on HRWs were COPD overview and medication administration, whereas three common sub-topic groups in HI needs among patients in the literature were COPD overview, self-management, and emotional management. Conclusion: The knowledge structure of HI on HRWs is medically oriented, while patients need supportive information. Thus, the support system for self-management and emotional management on HRWs must be informed according to the structure of patients' needs for HI. Healthcare providers should consider presenting COPD patient-centered information on HRWs.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1462-1468
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• 2022

Among the data used for the diagnosis of calf disease, feces play an important role in disease diagnosis. In the image of calf feces, the health status can be known by the shape, color, and texture. For the fecal image that can identify the health status, data of 207 normal calves and 158 calves with diarrhea were pre-processed according to fecal status and used. In this paper, images of fecal variables are detected among the collected calf data and images are trained by applying GLCM-CNN, which combines the properties of CNN and GLCM, on a dataset containing disease symptoms using convolutional network technology. There was a significant difference between CNN's 89.9% accuracy and GLCM-CNN, which showed 91.7% accuracy, and GLCM-CNN showed a high accuracy of 1.8%.

• Korean small business review
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• v.42 no.4
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• pp.235-250
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• 2020

This study surveyed the perception of university students about employment in Small and Medium-sized Enterprises(SME) in the Chungbuk area to prepare improvement measures. In particular, the data were collected in descriptive questions along with the existing survey methods, and the perception of SME and decent work was identified using text-mining. As a result of the analysis, there are positive perceptions of jobs at SME such as various work experiences and low job competition rates, while there are generally many negative perceptions in pay, work and welfare. However, as a result of co-occurrence network analysis of responses to decent jobs, 'Information' was derived as a keyword. Currently, college students' negative perception of SME is affected by the lack of sufficient information, which needs to be improved first. To solve this problem, it was proposed to establish and operate a platform that can provide information on employment of SME and select necessary personnel.

• Journal of the Korea Society of Computer and Information
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• v.26 no.12
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• pp.85-97
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• 2021

In this paper, in order to support rapid and effective decision-making and response in disaster situations, we identified the author's organization of academic research papers and conducted a collaborative relationship analysis study based on this. For this purpose, 2,308 papers in 69 Korean academic journals classified by disaster and safety type were selected for analysis and experimental data were constructed based on the Korea Science Citation Database (KSCD) and institutional identification data provided by KISTI. Collaborative relationship analysis was conducted for each of the four units (Institution, Institution type, Institution region and University department type). First, statistical status such as frequency of appearance was compared, and basic properties and main centrality index of each co-occurrence network were calculated and analyzed using Social Network Analysis Method. In addition, a visualization map was created and presented for each network so that the collaborative relationship could be viewed and understood as a whole. The results of this study are expected to contribute to the search activities of institutions and cooperative groups that support effective disaster response and to lay the foundation for the information service system.