• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.2
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• pp.139-145
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• 2024

This paper presents the design of a voltage controlled oscillator (VCO) which is one of the key building blocks in modern wireless communication systems with small VCO gain (K_vco) variation. To compensate conventional large K_vco variation, a series varactor bank has been added to the conventional LC-tank with parallel capacitor bank array. And also, in order to achieve excellent phase noise performance while maintaining wide tuning range, a mixed coarse/fine tuning scheme(series varactor array and parallel capacitor array) is chosen. The switched varactor array bank is controlled by the same digital code for switched capacitor array without additional digital circuits. For use at a low voltage of 1.2V, the proposed current reference circuit in this paper used a current reference circuit for safety with the common gate removed more safely. Implemented in a TSMC 0.13㎛ CMOS RF technology, the proposed VCO can be tuned from 4.4GH to 5.3GHz with the K_vco (VCO gain ) variation of less than 9.6%. While consuming 3.1mA from a 1.2V supply, the VCO has -120dBc/Hz phase noise at 1MHz offset from the carrier of the 5.3 GHz.

• Microbiology and Biotechnology Letters
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• v.51 no.4
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• pp.517-525
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• 2023

The emergence and spread of multidrug-resistant Pseudomonas aeruginosa (MRPA) have become a serious problem worldwide. The involvement of metallo-β-lactamases (MBLs) in inducing carbapenem resistance is particularly acute. However, unlike other members of the Enterobacteriaceae genus, new clones of P. aeruginosa are constantly emerging and rapidly replacing previously prevalent dominant clones. Therefore, this study aimed to perform antimicrobial resistance gene analysis, integron gene cassette analysis using DNA sequencing, and plasmid transfer analysis by conjugation to investigate the antimicrobial resistance dynamics of 18 P. aeruginosa strains isolated from various medical samples at a general hospital in Busan from September 2017 to September 2019. All 18 strains showed extensively drug-resistant (XDR) phenotype and were resistant to most antibiotics, except colistin (100%) but were susceptible to aztreonam (22.2%) and ceftazidime (16.6%). Approximately 66.7% of the strains had Class 1 integrons showing various antimicrobial resistances. Notably, IMP-6 ST235 (66.7%), VIM-2 ST357 (16.7%), and IMP-1 ST446(16.7%) were identified. The identification of IMP-1-producing ST446, previously unreported in Korea, is noteworthy considering the emergence and prevalence of another MRPA high-risk clone.

• Microbiology and Biotechnology Letters
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• v.51 no.4
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• pp.500-506
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• 2023

Carbapenem-resistant Klebsiella pneumoniae (CRKP) is emerging as a worldwide public health threat. Recently, Klebsiella pneumoniae carbapenemase-2 (KPC-2)-producing sequence type (ST) 307 was identified main clone of CRKP, and dissemination of ST307 was reported in South Korea. This study examined the molecular characteristic and antimicrobial resistance pattern of 50 CRKP isolated from a tertiary hospital in Daejeon, from March 2020 to December 2021. Epidemiological relationship was analyzed by Multilocus sequence typing (MLST) and antimicrobial susceptibility test was determined using disk-diffusion method. PCR and DNA sequence analysis were performed to identify carbapenemase genes. CRKP infections were significantly more frequent in males and the patients aged ≥ 60 years. Among the 50 CRKP isolates, 46 isolates (92.0%) were multidrug-resistant (MDR), and 44 isolates (88.0%) were carbapenemase-producing K. pneumoniae (CPKP). The major carbapenemase type was KPC-2 (36 isolates, 72.0%) and New Delhi metalloenzyme-1 (NDM-1) and NDM-5 were identified in 7 isolates (14.0%) and 1 isolate (2.0%), respectively. In particular, 88.9% (32/36) of KPC-2-producing K. pneumoniae belonged to ST307, whereas 87.5% (7/8) of NDM-1,-5-producing K. pneumoniae belonged to non-ST307. These results suggest that proper infection control and effective surveillance network need to prevent not olny the spread of ST307, but also the development of non-ST307.

• Korean Journal of Radiology
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• v.21 no.6
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• pp.670-683
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• 2020

Objective: The presence of coagulative necrosis (CN) in clear cell renal cell carcinoma (ccRCC) indicates a poor prognosis, while the absence of CN indicates a good prognosis. The purpose of this study was to build and validate a radiomics signature based on preoperative CT imaging data to estimate CN status in ccRCC. Materials and Methods: Altogether, 105 patients with pathologically confirmed ccRCC were retrospectively enrolled in this study and then divided into training (n = 72) and validation (n = 33) sets. Thereafter, 385 radiomics features were extracted from the three-dimensional volumes of interest of each tumor, and 10 traditional features were assessed by two experienced radiologists using triple-phase CT-enhanced images. A multivariate logistic regression algorithm was used to build the radiomics score and traditional predictors in the training set, and their performance was assessed and then tested in the validation set. The radiomics signature to distinguish CN status was then developed by incorporating the radiomics score and the selected traditional predictors. The receiver operating characteristic (ROC) curve was plotted to evaluate the predictive performance. Results: The area under the ROC curve (AUC) of the radiomics score, which consisted of 7 radiomics features, was 0.855 in the training set and 0.885 in the validation set. The AUC of the traditional predictor, which consisted of 2 traditional features, was 0.843 in the training set and 0.858 in the validation set. The radiomics signature showed the best performance with an AUC of 0.942 in the training set, which was then confirmed with an AUC of 0.969 in the validation set. Conclusion: The CT-based radiomics signature that incorporated radiomics and traditional features has the potential to be used as a non-invasive tool for preoperative prediction of CN in ccRCC.

• Geophysics and Geophysical Exploration
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• v.27 no.1
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• pp.23-36
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• 2024

In this study, we analyze the structure of the Korea-Japan Joint Development Zone (JDZ) using gravity, magnetic, and seismic data. Gravity and magnetic data analysis confirmed that the Jeju Basin exhibits low anomalies compared to adjacent areas. We applied the total gradient to the Bouguer anomaly to identify basin boundaries, and computed the analytic signal from the total magnetic anomaly data to enhance the edges of the magnetic anomalies. The Taiwan-Sinzi Belt, exhibits high magnetic anomalies and crosses the center of the JDZ in the northeast-southwest direction; we presume that intrusive rocks are sporadic in the JDZ. The 3D inversion results of the gravity and magnetic data show a strong correlation between magnetic susceptibility and density (i.e. a low-density zone in the Jeju Basin and the Ho Basin, and a high magnetic susceptibility distribution in the Taiwan-Sinzi Belt). Comparison of the density and seismic profiles of the Jeju Basin shows that high densities are associated with sill, horst, and basement highs, whereas low densities are associated with basement low and grabens. These results suggest that interpretations based on seismic, gravity and magnetic data can effectively reveal the subsurface structure of the JDZ.

• Tunnel and Underground Space
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• v.34 no.1
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• pp.1-14
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• 2024

An image-reconstruction technology, involving the deployment of an unmanned mobility equipped with high-speed LiDAR (Light Detection And Ranging) has been proposed to reconstruct the shape of abandoned mine. Unmanned mobility operation is remarkably useful in abandoned mines fraught with operational difficulties including, but not limited to, obstacles, sludge, underwater and narrow tunnel with the diameter of 1.5 m or more. For cases of real abandoned mines, quadruped robots, quadcopter drones and underwater drones are respectively deployed on land, air, and water-filled sites. In addition to the advantage of scanning the abandoned mines with 2D solid-state lidar sensors, rotation of radiation at an inclination angle offers an increased efficiency for simultaneous reconstruction of mineshaft shapes and detecting obstacles. Sensor and robot posture were used for computing rotation matrices that helped compute geographical coordinates of the solid-state lidar data. Next, the quadruped robot scanned the actual site to reconstruct tunnel shape. Lastly, the optimal elements necessary to increase utility in actual fields were found and proposed.

• Journal of the Society of Disaster Information
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• v.20 no.1
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• pp.106-116
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• 2024

Purpose: This paper conducts IoT and CCTV-based safety monitoring to analyze accidents and potential risks occurring at construction sites, and detect and analyze risks such as falls and collisions or abnormalities and to establish a system for early warning using devices like a walkie-talkie and chatbot service. Method: A safety management service model is presented through smart construction technology case studies at the construction site and review a relevant literature analysis. Result: According to 'Construction Accident Statistics,' in 2021, there were 26,888 casualties in the construction industry, accounting for 26.3% of all reported accidents. Fatalities in construction-related accidents amounted to 417 individuals, representing 50.5% of all industrial accident-related deaths. This study suggests implementing AI chatbot services for construction site safety management utilizing IoT-based health monitoring technologies in smart construction practices. Construction sites where stakeholders such as workers participate were demonstrated by implementing an artificial intelligence chatbot system by selecting major risk areas within the workplace, such as scaffolding processes, openings, and access to hazardous machinery. Conclusion: The possibility of commercialization was confirmed by receiving more than 90 points in the satisfaction survey of participating workers regarding the empirical results of the artificial intelligence chatbot service at construction sites.

• Knowledge Management Research
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• v.25 no.1
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• pp.193-215
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• 2024

This study aims to identify the main factors that caused the digital divide during the COVID-19 pandemic. Utilizing data from the 2020 and 2021 Digital Divide Surveys by the National Information Agency, a research model was constructed for analysis using SmartPLS 4, applying PLS-SEM and Multigroup Analysis methods. The results of the study are as follows. First, combining 2020 and 2021, mobile internet usage during COVID-19 is positively associated with digital skills, digital usage, and usage outcomes except for networking. Second, the impact of digital usage was significantly higher during the outbreak than during the beginning of COVID-19, which may be due to the increased demand for digital usage as the outbreak continued, and the corresponding increase in internet usage. Third, we discovered that demographics are not the main factor affecting changes in mobile internet use during the COVID-19 pandemic. Instead, digital literacy affects mobile usage, which is the most important one. The results show the importance of creating programs to teach people how to use technology appropriately. We propose that digital literacy should be central to training programs for people who use digital services.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.1
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• pp.129-141
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• 2024

Amidst the acceleration of digital transformation across various sectors, the financial market is increasingly focusing on the development of digital and electronic payment methods, including currency. Among these, Central Bank Digital Currencies (CBDC) are emerging as future digital currencies that could replace physical cash. They are stable, not subject to value fluctuation, and can be exchanged one-to-one with existing physical currencies. Recently, both domestic and international efforts are underway in researching and developing CBDCs. However, current CBDC systems face scalability issues such as delays in processing large transactions, response times, and network congestion. To build a universal CBDC system, it is crucial to resolve these scalability issues, including the low throughput and network overload problems inherent in existing blockchain technologies. Therefore, this study proposes a solution based on reinforcement learning for handling large-scale data in a CBDC environment, aiming to improve throughput and reduce network congestion. The proposed technology can increase throughput by more than 64 times and reduce network congestion by over 20% compared to existing systems.

• Nuclear Engineering and Technology
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• v.55 no.12
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• pp.4357-4366
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• 2023

MARS-KS, a domestic regulatory confirmatory code of Republic of Korea, had been developed by integrating RELAP5/MOD2 and COBRA-TF. The integration of COBRA-TF allowed to extend the capability of MARS-KS, limited to one-dimensional analysis, to multi-dimensional analysis. The use of COBRA-TF was mainly focused on subchannel analyses for simulating multi-dimensional behavior within the reactor core. However, this feature has been remained as a legacy without ongoing maintenance. Meanwhile, MARS-KS also includes its own multidimensional component, namely MULTID, which is also feasible to simulate three-dimensional convection and diffusion. The MULTID is capable of modeling the turbulent diffusion using simple mixing length model. The implementation of the turbulent mixing is of importance for analyzing the reactor core where a disturbing cross-sectional structure of rod bundle makes the flow perturbation and corresponding mixing stronger. In addition, the presence of this turbulent behavior allows the secondary transports with net mass exchange between subchannels. However, a series of assessments performed in previous studies revealed that the turbulence model of the MULTID could not simulate the aforementioned effective mixing occurred in the subchannel-scale problems. This is obvious consequence since the physical models of the MULTID neglect the effect of mass transport and thereby, it cannot model the void drift effect and resulting phasic distribution within a bundle. Thus, in this study, the turbulence mixing model of the MULTID has been improved by means of the inter-channel mixing model, widely utilized in subchannel analysis, in order to extend the application of the MULTID to small-scale problems. A series of assessments has been performed against rod bundle experiments, namely GE 3X3 and PSBT, to evaluate the performance of the introduced mixing model. The assessment results revealed that the application of the inter-channel mixing model allowed to enhance the prediction of the MULTID in subchannel scale problems. In addition, it was indicated that the code could not predict appropriate phasic distribution in the rod bundle without the model. Considering that the proper prediction of the phasic distribution is important when considering pin-based and/or assembly-based expressions of the reactor core, the results of this study clearly indicate that the inter-channel mixing model is required for analyzing the rod bundle, appropriately.