• Journal of Gastric Cancer
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• v.20 no.4
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• pp.385-394
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• 2020

Purpose: Patients with gastric cancer who receive neoadjuvant therapy are staged before treatment (cStage) and after treatment (ypStage). We aimed to compare the prognostic reliability of cStage and ypStage, alone and in combination. Materials and Methods: Data for all patients who received neoadjuvant therapy followed by surgery for gastric adenocarcinoma from 2004 to 2015 were extracted from the National Cancer Database. Kaplan-Meier (KM)curves were used to model overall survival based on cStage alone, ypStage alone, cStage stratified by ypStage, and ypStage stratified by cStage. P-values were generated to summarize the differences in KM curves. The discriminatory power of survival prediction was examined using Harrell's C-statistics. Results: We included 8,977 patients in the analysis. As expected, increasing cStage and ypStage were associated with worse survival. The discriminatory prognostic power provided by cStage was poor (C-statistic 0.548), while that provided by ypStage was moderate (C-statistic 0.634). Within each cStage, the addition of ypStage information significantly altered the prognosis (P<0.0001 within cStages I-IV). However, for each ypStage, the addition of cStage information generally did not alter the prognosis (P=0.2874, 0.027, 0.061, 0.049, and 0.007 within ypStages 0-IV, respectively). The discriminatory prognostic power provided by the combination of cStage and ypStage was similar to that of ypStage alone (C-statistic 0.636 vs. 0.634). Conclusions: The cStage is unreliable for prognosis, and ypStage is moderately reliable. Combining cStage and ypStage does not improve the discriminatory prognostic power provided by ypStage alone. A ypStage-based prognosis is minimally affected by the initial cStage.

• Journal of the Korean Geosynthetics Society
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• v.20 no.1
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• pp.21-34
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• 2021

In this study, to solve a problem that cannot consider the contribution effect of each layers when the apparent earth pressure in homogeneous ground is applied to multi-layered ground, the measured earth pressures at World were investigated and analyzed. It has been confirmed that the apparent earth pressure in mulit-layered ground is different from single ground and that the extra layer's contribution to the earth pressure cannot be considered. The conventional method of calculating the apparent earth pressure for single ground was extended to mulit-layered ground, and proposed and verified the applicable method for both single and mulit-layered ground. The proposed methods predicted the earth pressure closer to the measurements at the excavation depth of 0.1Z/H or below, and the prediction reliability was evaluated to be better than the conventional method. Among the proposed methods, the method of considering the area ratio of the active failure has a geotechnical validity and predicts the most similar results to the actual earth pressure. To confirm the applicability of the proposed methods, it was presented by comparing and analyzing the results of the proposed methods with the conventional method for the actual case.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.3
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• pp.471-476
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• 2021

Soft magnetic composite (SMC) materials based on powder metallurgy have a number of advantages over the conventional electrical steel sheets commonly used in electric machines. Thus, technologies related to these materials have shown significant improvement in recent years. In general, SMCs are magnetically isotropic owing to the shape of the powder, which makes them suitable for the construction of electric machines with three-dimensional flux and complex structures. However, the materials with isotropic magnetic properties (such as SMCs) have complex vector hysteresis; thus, it is very difficult to predict accurate loss properties. Therefore, we manufactured ring-type specimens of electrical steel sheets and SMC, which analyzed their magnetic properties according to the specimen size, and performed the electromagnetic field analysis of a high-speed permanent magnet (PM) motor driven at 800 Hz or higher using the measured magnetic information to compare the core loss of the motor. The reliability of this paper has been verified by measuring the efficiency after manufacturing the motor.

• Journal of Physiology & Pathology in Korean Medicine
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• v.36 no.3
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• pp.94-99
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• 2022

The discovery of biomarkers related to pattern identification (PI), the core diagnostic theory of Korean medicine (KM), is one of the methods that can provide objective and reliable evidence by applying PI to clinical practice. In this study, 40 diabetic patients and 41 healthy control subjects recruited from the Korean medicine clinic were examined to determine the human electrical response related to the deficiency pattern, a representative pattern of diabetes. Qi-Blood-Yin-Yang deficiency pattern scores, which are representative deficiency patterns for diabetes mellitus, were obtained through a questionnaire with verified reliability and validity, and the human electrical response was measured non-invasively using a bioimpedance meter. In ANCOVA analysis using gender as a covariate, the 5 kHz frequency resistance and 5-250 kHz frequency reactance were significantly lower in the diabetic group than in non-diabetic control group. In addition, the multiple regression analysis showed a positive correlation (R2=0.11~0.19) between the Yang deficiency pattern score and resistance value for the diabetic group; the correlation was higher at higher frequencies of 50kHz (R2=0.18) and 250kHz (R2=0.19) compared to 5kHz(R2=0.11). In contrast, there was no such significant association in the control group. It implies that bioimpedance resistance measured at finite frequencies may be useful in predicting Yang deficiency, which is closely related to diabetic complications by reflecting the decrease in body water content and metabolism. In the future, large-scale planned clinical studies will be needed to identify biomarkers associated with different types of PI in diabetes.

• The Journal of the Convergence on Culture Technology
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• v.8 no.4
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• pp.407-413
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• 2022

In this study, the empirical formula for evaluating cable tension based on long-term measurement for about 3 years according to temperature change was proposed by proving the correlation between the expansion joint displacement of the upper road bridge and the cable tension of the lower railway bridge. The tension prediction results using the empirical formula for tension evaluation each cables proposed in this study were found to be in good agreement with the cable tension using the vibration method within 3%. Therefore, it was analyzed that it could be applied together with the vibration method that was an experimental technique, to predict and evaluate the cable tension in serviced railway steel composite bridge. As a result of applying the estimated temperature calculated by the empirical formula for expansion proposed in this study to the empirical formula, it was analyzed that a high level of reliability could be secured when compared with the vibration method. Therefore, it is judged that the empirical formula for cable tension evaluation reflecting the estimated temperature proposed in this study can be used to predict the tension of cables according to climate change in the future and establish a maintenance plan.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.294-302
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• 2022

Detection of fake news is a complex and a challenging task. Generation of fake news is very hard to stop, only steps to control its circulation may help in minimizing its impacts. Humans tend to believe in misleading false information. Researcher started with social media sites to categorize in terms of real or fake news. False information misleads any individual or an organization that may cause of big failure and any financial loss. Automatic system for detection of false information circulating on social media is an emerging area of research. It is gaining attention of both industry and academia since US presidential elections 2016. Fake news has negative and severe effects on individuals and organizations elongating its hostile effects on the society. Prediction of fake news in timely manner is important. This research focuses on detection of fake news spreaders. In this context, overall, 6 models are developed during this research, trained and tested with dataset of PAN 2020. Four approaches N-gram based; user statistics-based models are trained with different values of hyper parameters. Extensive grid search with cross validation is applied in each machine learning model. In N-gram based models, out of numerous machine learning models this research focused on better results yielding algorithms, assessed by deep reading of state-of-the-art related work in the field. For better accuracy, author aimed at developing models using Random Forest, Logistic Regression, SVM, and XGBoost. All four machine learning algorithms were trained with cross validated grid search hyper parameters. Advantages of this research over previous work is user statistics-based model and then ensemble learning model. Which were designed in a way to help classifying Twitter users as fake news spreader or not with highest reliability. User statistical model used 17 features, on the basis of which it categorized a Twitter user as malicious. New dataset based on predictions of machine learning models was constructed. And then Three techniques of simple mean, logistic regression and random forest in combination with ensemble model is applied. Logistic regression combined in ensemble model gave best training and testing results, achieving an accuracy of 72%.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.165-170
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• 2022

The amount of data generated by recent developments in Big data and related technologies has been rapidly increasing, and the need to predict changes in future societies and present technologies to be realized has been continuously raised to lay the foundation for national scientific and technological planning. The existing methods of predicting future technologies have their respective advantages, but problems also exist. Thus, this paper newly establishes and applies the methodology to be used for predicting future technologies specialized in information security fields beyond the existing comprehensive prediction, and draws out innovative technologies that are expected to have high ripple effects in the future, and analyzes the technological diffusion points of each technology to predict future technological changes in the information security sector. It is expected that this will ensure reliability and objectivity of the forecast survey results and allow more sophisticated and multilayered predictions than the overall scientific and technological forecast surveys.

• Nuclear Engineering and Technology
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• v.54 no.5
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• pp.1914-1928
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• 2022

To improve the heat transfer efficiency of the reactor fuel assembly, it is necessary to accurately calculate the two-phase flow boiling characteristics and the critical heat flux (CHF) in the fuel assembly. In this paper, a Eulerian two-fluid model combined with the extended wall boiling model was used to numerically simulate the 5 × 5 fuel rod bundle with spacer grids (four sets of mixing vane grids and four sets of simple support grids without mixing vanes). We calculated and analyzed 11 experimental conditions under different pressure, inlet temperature, and mass flux. After comparing the CHF and the location of departure from the nucleate boiling obtained by the numerical simulation with the experimental results, we confirmed the reliability of computational fluid dynamic analysis for the prediction of the CHF of the rod bundle and the boiling characteristics of the two-phase flow. Subsequently, we analyzed the influence of the spacer grid and mixing vanes on the void fraction, liquid temperature, and secondary flow distribution. The research in this article provides theoretical support for the design of fuel assemblies.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.6
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• pp.1193-1204
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• 2021

In information security, AI technology is used to detect unknown malware. Although AI technology guarantees high accuracy, it inevitably entails false positives, so we are considering introducing XAI to interpret the results predicted by AI. However, XAI evaluation studies that evaluate or verify the interpretation only provide simple interpretation results are lacking. XAI evaluation is essential to ensure safety which technique is more accurate. In this paper, we interpret AI results as features that have significantly contributed to AI prediction in the field of malware, and present an evaluation method for the interpretation of AI results. Interpretation of results is performed using two XAI techniques on a tree-based AI model with an accuracy of about 94%, and interpretation of AI results is evaluated by analyzing descriptive accuracy and sparsity. As a result of the experiment, it was confirmed that the AI result interpretation was properly calculated. In the future, it is expected that the adoption and utilization of XAI will gradually increase due to XAI evaluation, and the reliability and transparency of AI will be greatly improved.

• Journal of the Korea Society of Computer and Information
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• v.28 no.2
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• pp.39-46
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• 2023

We present an efficient packet transmission strategy for massively multiplayer online first-person shooter (MMOFPS) games using movement-adaptive packet transmission interval. The player motion in FPS games shows a wide spectrum of movement variability both in speed and orientation, where there is room for reducing the number of packets to be transmitted to the server depending on the predictability of the character's movement. In this work, the degree of variability (nonlinearity) of the player movements is measured at every packet transmission to calculate the next transmission time, which implements the adaptive transmission frequency according to the amount of movement change. Server-side prediction with a few auxiliary heuristics is performed in concert with the incoming packets to ensure reliability for synchronizing the connected clients. The comparison of our method with the previous fixed-interval transmission scheme is presented by demonstrating them using a test game environment.