This study examines how digital transformation technology (DTT) adoption affects the speed of total factor productivity (TFP) convergence using Korean firm-level data from 2017 to 2023. We confirm the presence of TFP convergence in both manufacturing and non-manufacturing sectors. We find that DTT adoption is associated with higher TFP growth in both sectors. However, the speed of convergence slows as DTT intensity increases, and this pattern is more pronounced among manufacturing firms. Overall, we provide additional evidence and new insights into how technological progress is linked to productivity dynamics and convergence patterns across sectors. We also highlight sector-level differences in the relationship between DTT diffusion, TFP growth, and catch-up processes.

This study investigates an ammonia-hydrogen dual-fuel spark ignition engine to overcome the limitations of ammonia fuel, such as low reactivity and narrow flammability limits. Combustion analysis for pure ammonia established baseline conditions, followed by simulations applying hydrogen fraction from ammonia decomposition. As the hydrogen fraction increased to 60 %, brake torque improved by 186 %, brake thermal efficiency rose by 138 %, and brake specific fuel consumption decreased by 79 % versus the ammonia-only baseline. Computational fluid dynamics results visualized combustion and emission behavior, showing that hydrogen enrichment reduced ignition delay and enhanced combustion completeness, while nitrogen oxides emissions rose due to higher temperatures. A trade-off analysis identified optimal hydrogen ratios of 39 % at 100 kg/h and 29 % at 140 kg/h airflow, balancing performance and emissions. These results highlight the potential of ammoniahydrogen dual-fuel operation as a carbon-free engine solution, demonstrating substantial gains in performance and combustion stability.

NOx, which is generated in high-temperature combustion environments, is a significant environmental pollutant that has led to stricter regulations on its emissions. This study experimentally demonstrated the effectiveness of the pulsating combustion for NOx reduction in a 240 kWth furnace. A detailed chemical reaction mechanism, GRI 3.0, was integrated with a 3-D transient CFD analysis and 0-D PSR modeling to analyze the NOx production and decomposition mechanisms during pulsating combustion. The experimental results showed that NOx emissions were reduced by 4-30% compared to non-pulsating conditions, depending on the valve opening cycle and duty ratio. This reduction was attributed to a combination of decreased fuel flow and the cyclical repetition of the relatively lean-rich combustion conditions induced by the pulsating variables. As the local equivalence ratio fluctuated, the NO to NO2 oxidation reaction became more active during the valve-closing phase, when the fuel flow decreased and lean conditions dominated. Conversely, during the valve-opening phase, when pressurized fuel is rapidly injected under rich conditions, NO2 is primarily reduced to NO in conjunction with the production of OH radicals. Therefore, to identify the optimal pulsating conditions, it is crucial to maintain lean conditions for as long as possible, which can be achieved by increasing the duration of the closed-valve phase within each cycle and effectively maintaining a high duty ratio. Pulsating combustion technology has been confirmed as a method that can significantly reduce NOx emissions without replacing legacy burners. This technique can be applied to industrial furnaces by simply applying a pulsating system.

Nitrogen oxides (NOx), classified as an indirect greenhouse gas (GHG), are increasing in demand for reduction as emission regulations are expanded not only in internal combustion engines but also throughout the industry. Nitrogen atoms are dissociated at relatively low temperature and can be easily converted to NOx by radicals and intermediates, so the reaction pathway is complex and changes in a short time. Therefore, numerical analysis methods should be used to simulate combustion phenomena and analyze chemical reactions, emphasizing the importance of the reaction mechanism, which includes reaction constants and reaction pathways. In this study, the laminar premixed flame was simulated using a numerical analysis method, and the NOx formation characteristics were identified according to the analysis variables using a reaction mechanism. The study was carried out using GRI 3.0, Okafor, and Konnov 0.5, which includes the combustion reaction of methane, as the variables used were equivalence ratio and inlet temperature. As a result, it was confirmed that Konnov 0.5 generates less NOx compared to GRI 3.0 and Okafor. Upon analyzing the reaction contribution, it became apparent that the hydrocarbon chain and chain-branching reaction and the third-body efficiency coefficient contribute to Konnov 0.5's NOx generation. The results in one and two dimensions showed similar trends. It is expected that similar results will be obtained for higher-dimensional systems with complex physical phenomena.

This study investigates the reasons behind the slowdown in real wages for Japan and Korea based on the aggregate and industry-level data for the respective countries. The findings suggest the following. First, both at the aggregate and industry level, there is a significant slowdown in both countries in the post-1995 period regarding labor productivity, which explains the overall slowdown in real wages. Second, the main reason for the gap between the growths in real wages and labor productivity is found to be the changes in the labor's terms of trade, which is defined as the consumer price index to GDP deflator ratio. Thus, the wage-labor productivity gap is not systematically connected to changes in labor income shares. Finally, the fall in the labor's terms of trade may be potentially related to an emphasis on exports and strong technological upgrading toward higher productivity growth products in both countries' economic development.

This study assessed the factors allowing middle-income countries to achieve higher income levels and thus escape the middle-income trap (MIT). By deriving a stochastic production function using the Cornwell-Schmidt-Sickles (CSS) estimator and country panel data, we successfully distinguished between growth due to total factor productivity (TFP) and that attributable to various production inputs after controlling for random shocks and cross-sectional dependence. We found that TFP growth was the main factor distinguishing middle-income countries that have and have not escaped from the MIT; the former countries had significantly higher TFP growth.

The icing of an intake pipe that might happen in an actual vehicle was numerically predicted in this study. For various operating conditions, the amount of icing was estimated, and the variables influencing the amount of icing were identified. We compared the factors that affected icing: relative humidity, air temperature, and inlet velocity. Seven RPM and load conditions, an intake temperature range of 253–268 K, and a relative humidity range of 65–85% were used for the case studies. To verify the model accuracy, wind tunnel test results from chassis dynometer tests were compared to the data from simulations. The flow analysis was performed using the numerical analytical tool ANSYS Fluent (2019 R1), while the amount of condensed water and icing was predicted using FENSAP-ICE, a program that analyzes and predicts icing phenomena under mechanical systems. The ambient temperature, relative humidity, and inlet air velocity had the biggest effects on the icing rate. The total amount of icing increased for similar BB and input air velocities. When the input air and BB velocities are the same, the variables influencing icing are the ambient temperature and relative humidity. The amount of ice was less affected by outside temperature and relative humidity when the rpm was high, and the inlet air velocity also had an impact.

In order to directly apply ammonia as main fuel, research is being actively conducted on NOx reduction technology, which is the main emission from exhaust gas. When ammonia is used as fuel and simultaneously injected into the combustion chamber not only as a main fuel, but also as a reducing agent, a phenomenon similar to the SNCR effect that reduces NOx can be observed. This study objects to improve NOx reduction efficiency in ammonia swirl burners. To observe changes in performance, analysis was performed by changing the secondary injection of ammonia flow rate and injection angle using CONVERGE. As a result, the NOx reduction efficiency could be observed from approximately 69% to 99% depending on each variable, and the secondary ammonia injection flow rate could be optimized according to the secondary ammonia injection angle.

NOx contributes to the formation of ozone, a major greenhouse gas, through photochemical reactions in the atmosphere, and also causes acid rains. Therefore, there is a growing demand for reducing nitrogen oxides. NOX is actively generated at fuel-lean and high temperatures. Therefore, combustion near the stoichiometry ratio and avoiding the peak combustion temperature are reduction methods. Moreover, NOX can be classified into fuel NOX, thermal NOX, and prompt NOX according to the cause and characteristics of their occurrence. Ongoing research is analyzing key reactions that contribute to the formation of NOX and simulating phenomena via numerical analysis research to seek reduction measures. Therefore, the significance of the detailed and consistent reaction mechanism is increasing. The Okafor mechanism simulates a granular combustion reaction of methane and ammonia and better simulates the effect of the radical-based species on the formation of NOX based on the GRI 3.0 mechanism and Tian mechanism. The present study aims to analyze the key reactions of NOX formation through Okafor mechanism in the laminar flame of methane, to analyze the effect of oxidant concentration and pre-heating temperature on NOX formation. Numerical analysis research based on Okafor mechanism is expected to be useful to analyze the phenomenological causes of NOX formation.

Federated learning has become popular nowadays since being started by Google in developing their Google Keyboard solution. Original federated learning proposed how to secure aggregating the gradient from the local training process of joining mobile devices. However, other machine mechanisms without gradient updating, such as random forest, are not supported. In this work, we propose PriForest, a new approach for building random forest in the federated learning setting. This framework covers all random forest processes, including building the forest, updating the forest, and using the forest for prediction. For providing privacy reserving, we apply a differential-privacy scheme while making bootstrapping sets, which modifies the value of existing records or appends new records before constructing trees. The experiment result shows that our approach is applicable with an affordable noise rate, which controls the sensitivity of the noise adding method.

This study proposes an effective repair technology using arc additive manufacturing for pressurized water reactors (PWRs) in nuclear power plants (NPP) aimed at avoiding complete replacements and post-weld-heat treatments (PWHTs) of component parts while ensuring safety and reliability. Effective repair technology is defined as economic and process efficiency, because of maintenance costs and radiation exposure, and it is critical in related industries. The technology is designed to relieve the hardness and martensite fraction of the welding heat affected zone (HAZ) of low alloy steels (SA508) in PWRs penetration/nozzles by heat source generated in the WAAM process, thus ensuring structural integrity. In the first layer of wire arc additive manufacturing processes, 89.6% of the martensite phase was formed in the HAZ of SA508, which was significantly reduced to 45.7% due to repetitive thermal behaviors at the third layer. The resulting process dramatically reduced hardness from 450Hv in the initial layer additive manufacturing to 320Hv in 3 layers without additional heat treatments. Moreover, the study quantitatively investigated the martensite starting temperature (Ms) and bainite starting temperature (Bs) and analyzed the microstructure and mechanical behavior of the developed process using thermodynamic calculation (CALPHAD), finite element method (FEM) simulation, and microstructure quantitative analysis by electron backs-catter diffraction (EBSD). The proposed technologies and their quantitative analysis results can be a substantial alternative to the repair technology for penetration/nozzles in nuclear primary water cooling reactor applications, complying with ASME Sec.IX Qw-462.12 and ISO 15614-1.

Due to the significant growth of computing devices, attacks on the network have received increasing consideration. In traditional anomaly detection methods, an agent must collect all data to train the model, potentially leading to data leakage. Thus, the security challenges have encouraged the use of federated learning to address this issue by anomaly detection while improving the efficiency and privacy of the training models. However, in an extensive network, the imbalance of data in the training set for each client and the large volume of data point distribution between classes are significant challenges for training models. Thus, it is necessary to re-balance the training dataset before anomaly tasks. In this paper, we propose a re-balancing scheme for mitigating the impact of imbalanced training data. This work combines k-nearest neighbors with the Tomek link synthetic minority oversampling method. While Tomek Link eliminates a pair of samples from two distinct classes (one majority class and one minority class) that are closest, k-nearest neighbors enrich the minority class by providing artificial examples in the minority class. Tomek link makes advantage of minority class data that k-SMOTE oversampled to obtain more accurate class clusters. Our experiments demonstrate the importance of acknowledging class imbalance.

It finds that financial uncertainty has a significant negative effect on corporate investment and the effects are mixed across firms of different sizes. Small firms and large firms are more exposed to the negative uncertainty effects than medium-sized firms. Financial constraints and investment irreversibility amplify the negative effects of uncertainty. Small and medium-sized firms are more financially constrained and large firms’ investments are more irreversible in nature. The authors suggest that policies target the development of capital markets and bond markets for small and medium-sized firms and focus on competitiveness, not protection.

This study examines the association between local currency (LCY) bond market development and currency stability. Using data from global economies, this study finds that in economies with more developed LCY bond markets, exchange rate volatility is lower during market turmoil. Currency volatility is lowered in bond markets with a greater share of LCY bonds and long-term bonds, even during normal times. The findings suggest that LCY bond market development contributes to financial stability especially during stress times.

Low-pressure exhaust gas recirculation (LP-EGR) systems are applied to diesel engines because they reduce nitrogen oxide emission by lowering the internal temperature of the cylinder by mixing the oxides with intake air. However, low-temperature ambient conditions include a large amount of vapor in the mixed gas flowing into the intercooler; when heat is exchanged, the water vapor condenses and is adsorbed on the surface of the intercooler fin to form a liquid film. Condensation occurs as the thermal resistance between the vapor and solid surface increases with the thickness of the liquid film and causing a corrosion due to condensation of the surface. In this study, the amount of condensation was predicted through calculations based on thermodynamic studies. Factors that can cause condensation inside the intercooler (fuel, air, and LP-EGR) were selected as variables. A mathematical formula was established to predict the convergence form of condensation or the amount of condensation over time at various temperature and relative humidity conditions. The formula predicted the condensation amount in the intercooler of the diesel engine, compared it to the actual amount of condensation in the test evaluation with an error of less than 4%. Additionally, because the formula can predict the amount of condensation by changing the heat exchange area of the intercooler, the application range of the formula was expanded to predict the condensation in the intercoolers of gasoline vehicles with different heat exchange areas and fuel types. The condensation error was within 2%, indicating a high consistency. Validation of the formula predicts a reliable amount of condensation under various operating and ambient temperature conditions, which means that both the time and cost of the test evaluation require the determination of the cause before solving the actual condensation problem.