• Journal of Satellite, Information and Communications
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• v.9 no.2
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• pp.18-22
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• 2014

Satellite communications consist of communications between base stations of the ground and satellites. For efficient satellite communications, ground networks should be organically utilized. Grid networks are frequently used in and outside the country for wireless communications. The performance of wireless communications is determined by mobility, topography, and jamming signals. Therefore, continuous studies of grid networks are necessary for the utilization of next period satellite networks. Since military communications are used based on wireless systems, they can be considered as a sample of utilization of grid networks. Therefore, this paper presented the results of simulations conducted for the improvement of the performance of the grid networks used in military communications that employing the OSPF, a popular routing protocol for military applications. First we investigate the effects of changing the bit error rate (BER) and number of routers. Then we discuss the effects of maximum segment size (MSS) on network behavior and stability. In this way, we can determine the appropriate MSS for a grid network under various values of BER and number of routers. Such results can be also applied to commercial grid network evaluations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.2
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• pp.365-371
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• 2015

CB tree represents the binary trie by a compact binary sequence. However, retrieval time grows fast since the more keys stored in the trie, longer the binary sequences are. In addition it is inefficient for frequent key insertion/deletion. HCB tree is a hierarchical CB tree consisting of small binary tries. However it can not avoid shift operations and have to scan an additional table to refer child or parent trie. In order to improve retrieval performance and avoid shift operations when keys are inserted or deleted, we in this paper represent each separated trie by a full binary trie and then assign the unique identifier to it. Finally the theoretical evaluations show that both the proposed approach and HCB tree provides better than CB tree for key retrieval. The proposed approach shows the highest performance in case of key insertion/deletion and moreover requires only 71%~89% of storage as compared with CB tree.

• Investigative Magnetic Resonance Imaging
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• v.23 no.3
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• pp.241-250
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• 2019

Purpose: The purpose of this study was to determine the relation between quantitative magnetic resonance imaging biomarkers, and clinical performances in chronic phase of carbon monoxide intoxication. Materials and Methods: Eighteen magnetic resonance scans and cognitive evaluations were performed, on patients with carbon monoxide intoxication in chronic phase. Apparent diffusion coefficient (ADC) ratios of affected versus unaffected centrum semiovale, and corpus callosum were obtained. Signal intensity (SI) ratios between affected centrum semiovale, and normal pons in T2-FLAIR (fluid-attenuated inversion recovery) images were obtained. The Mini-Mental State Exam, and clinical outcome scores were assessed. Correlation coefficients were calculated, between MRI and clinical markers. Patients were further classified into poor-outcome and good-outcome groups based on clinical performance, and imaging parameters were compared. T2-SI ratio of centrum semiovale was compared, with that of 18 sex-matched and age-matched controls. Results: T2-SI ratio of centrum semiovale was significantly higher in the poor-outcome group, than that in the good-outcome group and was strongly inversely correlated, with results from the Mini-Mental State Exam. ADC ratios of centrum semiovale were significantly lower in the poor outcome group than in the good outcome group, and were moderately correlated with the Mini-Mental State Exam score. Conclusion: A higher T2-SI and a lower ratio of ADC values in the centrum semiovale, may indicate presence of more severe white matter injury and clinical impairment. T2-SI ratio and ADC values in the centrum semiovale, are useful quantitative imaging biomarkers for correlation with clinical performance in individuals with carbon monoxide intoxication.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.4
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• pp.365-373
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• 2019

An Image Infra-Red(IIR) seeker is widely used for precision guided munitions to provide intelligent and precise target detection in terms of high kill probability. However, there have been issues in determining the performance versus cost trade-offs due to high cost of seeker comparing to other units of the munitions. In this paper, performance/cost evaluations have been carried out to find the most cost-effective solution for developing the IIR seekers. The relationships between the critical parameters and cost are investigated to determine the optimal point which represents the low cost with high performance. It is expected that the presented approach will be able to be used for guidelines to select the appropriate IIR seeker for the given operating conditions and can be useful to estimate the cost effectiveness of the precision guided munitions at early design stage.

• Land and Housing Review
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• v.13 no.4
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• pp.125-134
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• 2022

Reclaimed aggregates through waste asphalt are produced and utilized for waste resource utilization. This study conducts quality tests and performance evaluations for mixtures with Rejuvenator applied to reclaimed asphalt concrete. Through quality testing and performance evaluation, the study investigates whether there is any problem in using reclaimed asphalt concrete by replacing general hox mix asphalt. As a result, the values of ordinary hot mix asphalt are similar to those of reclaimed asphalt, suggesting that the substitution does not create critical engineering issues. Using reclaimed asphalt concrete has the advantages of increasing economic efficiency and utilizing waste resources.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.32 no.1
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• pp.53-63
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• 2022

Objectives: This study was designed to evaluate the filtration efficiency, inhalation resistance, and liquid resistance of commercial reusable masks in comparison to the performance of KF-AD masks (reference masks). Methods: Thirty-six masks were purchased from an online market. Filtration efficiency and inhalation resistance were determined in the same manner as in MFDS certification testing, respectively using TIL/IL & Filter Test 1300S (SFP Services, UK) and Breathing Resistance Analyzer DA2001 (Lambda Ray, South Korea). Results: Most of the filtration efficiencies found for the 19 masks were far lower than the test standard for KF-certified masks. Four masks met KF94 and three masks even met KF80. Most inhalation resistances were also much lower than the standard, with many almost one-half of the standard. In addition, all the masks except KF-AD masks did not pass the liquid resistance test. Conclusions: Although most of the filtration efficiency performance results found in this study for the reusable masks, which emerged as an alternative, were lower than the standard for health masks, multi-use masks can be used with a replacement filter inserted.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.741-747
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• 2022

Fatigue lowers an individual's ability and makes it difficult to perform work. As fatigue accumulates, concentration decreases and thus the possibility of causing a safety accident increases. Awareness of fatigue is subjective, but it is necessary to quantitatively measure the level of fatigue in the actual field. In previous studies, it was proposed to measure the level of fatigue by expert judgment by adding objective indicators such as bio-signal analysis to subjective evaluations such as multidisciplinary fatigue scales. However this method is difficult to evaluate fatigue in real time in daily life. This paper is a study on the fatigue classification model that determines the fatigue level of workers in real time using speech data recorded in the field. Machine learning models such as logistic classification, support vector machine, and random forest are trained using speech data collected in the field. The performance evaluation showed good performance with accuracy of 0.677 to 0.758, of which logistic classification showed the best performance. From the experimental results, it can be seen that it is possible to classify the fatigue level using speech signals.

• Computers and Concrete
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• v.32 no.2
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• pp.149-163
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• 2023

One of the main design parameters traditionally utilized in projects of geotechnical engineering is the uniaxial compressive strength. The present paper employed three artificial intelligence methods, i.e., the stochastic fractal search (SFS), the multi-verse optimization (MVO), and the vortex search algorithm (VSA), in order to determine the compressive strength of concrete (CSC). For the same reason, 1030 concrete specimens were subjected to compressive strength tests. According to the obtained laboratory results, the fly ash, cement, water, slag, coarse aggregates, fine aggregates, and SP were subjected to tests as the input parameters of the model in order to decide the optimum input configuration for the estimation of the compressive strength. The performance was evaluated by employing three criteria, i.e., the root mean square error (RMSE), mean absolute error (MAE), and the determination coefficient (R²). The evaluation of the error criteria and the determination coefficient obtained from the above three techniques indicates that the SFS-MLP technique outperformed the MVO-MLP and VSA-MLP methods. The developed artificial neural network models exhibit higher amounts of errors and lower correlation coefficients in comparison with other models. Nonetheless, the use of the stochastic fractal search algorithm has resulted in considerable enhancement in precision and accuracy of the evaluations conducted through the artificial neural network and has enhanced its performance. According to the results, the utilized SFS-MLP technique showed a better performance in the estimation of the compressive strength of concrete (R²=0.99932 and 0.99942, and RMSE=0.32611 and 0.24922). The novelty of our study is the use of a large dataset composed of 1030 entries and optimization of the learning scheme of the neural prediction model via a data distribution of a 20:80 testing-to-training ratio.

• The Journal of the Korea Contents Association
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• v.22 no.5
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• pp.26-36
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• 2022

Recently, studies have been conducted to cluster vehicles and disseminate safety messages in a VANET environment for driver safety and smoothy traffic. This paper proposes cluster management scheme for safety message dissemination through V2V communication and V2I communication in a VANET environment with high vehicle density and mobility. The proposed scheme reduces packet loss by selecting CH considering reception quality, total data owned by vehicles, moving speed, and connected vehicles, and maintaining cluster head candidates, which are the main agents of message dissemination, considering frequent cluster departures and subscriptions. In addition, the proposed scheme reduces duplicate messages by utilizing clusters by collaborating with a Road side unit(RSU). To prove the excellence of the proposed scheme, various performance evaluations are performed in terms of message packet loss and the number of RSU processing requests. As a result of performance evaluation, the cluster management scheme proposed in this paper shows better performance than the existing scheme.

• Korean Journal of Clinical Laboratory Science
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• v.56 no.2
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• pp.105-114
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• 2024

Clinical laboratories endeavor to secure quality by establishing effective quality management systems. However, laboratory environments are complex, and single quality control procedures may inadequately detect many errors. Patient-based real-time quality control (PBRTQC) is a laboratory tool that monitors the testing process using algorithms such as Bull's algorithm and several variables, such as average of normal, moving median, moving average, and exponentially weighted moving average. PBRTQC has many advantages over conventional quality control, including low cost, commutability, continuous real-time performance monitoring, and sensitivity to pre-analytical errors. However, PBRTQC is not easily implemented as it requires statistical algorithm selection, the design of appropriate rules and protocols, and performance verification. This review describes the basic concepts, methods, and procedures of PBRTQC and presents guidelines for implementing a patient-based quality management system. Furthermore, we propose the combined use of PBRTQC when the performance of internal quality control is limited. However, clinical evaluations were not conducted during this review, and thus, future evaluation is required.