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The purpose of this study was to classify Korean readers into subgroups based on their reading achievement and to examine the relationships between these subgroups and a set of cognitive-linguistic variables. The reading achievement and cognitive-linguistic skills of 394 elementary school students were measured and the data were analyzed by disaggregating into primary grade level (i.e., Grades 1-3) and intermediate grade level (i.e., Grades 4-6). The main results are summarized as follows. First, three subgroups of readers were found based on the reading achievement for the primary grade level: "very poor word readers and poor comprehenders," "poor readers," and "average readers." Second, four subgroups of readers were found based on the reading achievement for the intermediate grade level: "very significantly poor readers," "very poor readers," "average word readers but poor comprehenders," and "average readers." Third, vocabulary, rapid naming, phonological memory, and phonological awareness were cognitive-linguistic variables that significantly differentiated "very poor readers" and "poor readers" from "average readers" for the primary grade level. Fourth, phonological memory, rapid naming, sentence repetition, and listening comprehension were cognitive-linguistic variables that significantly differentiated "very poor readers" and "poor readers" from "average readers" for the intermediate grade level. This article also discusses the limits of this research and the implications in practice. Finally, this article touches upon the direction of future studies.

The surface treatment for a polymer‐ceramic composite is additionally performed in advanced material industries. To prepare the composite without a surface treatment, the simplest way to manufacture an advanced ceramic‐particle is devised. The method is the formation of a nanocrystalline composite layer through the simple liquid‐phase sintering. Using magnesia (MgO) which shows hydrophilicity, a nanocrystalline surface layer is realized by liquid‐phase sintering. The amorphous matrix of nanocrystalline composite layer makes MgO hydrophobic and ensures miscibility with polymers, and the nanocrystalline MgO ensures high thermal conductivity. In addition, the liquid phase removes the open pores and makes the surface morphology smooth MgO with smooth surface (MgO‐SM). Thermal interface materials (TIM) prepared with MgO‐SM and epoxy show a high thermal conductivity of ≈7.5 W m−1K−1, which is significantly higher than 4.5 W m−1K−1 of pure MgO TIM. Consequently, the formation process of a nanocrystalline surface layer utilizing simple liquid‐phase sintering is proposed as a fabrication method for a next‐generation ceramic‐filler. In addition, it is fundamentally identified that the thermal conductivity of MgO depends on the Mg deficiency, and therefore a poly‐crystal MgO‐SM (produced at a low temperature) has a higher thermal conductivity than a single‐crystal MgO (produced at a high temperature). [ABSTRACT FROM AUTHOR]

Objectives: This study aimed to build a comprehensive deep-learning model for the prediction of radiation pneumonitis using chest computed tomography (CT), clinical, dosimetric, and laboratory data. Introduction: Radiation therapy is an effective tool for treating patients with lung cancer. Despite its effectiveness, the risk of radiation pneumonitis limits its application. Although several studies have demonstrated models to predict radiation pneumonitis, no reliable model has been developed yet. Herein, we developed prediction models using pretreatment chest CT and various clinical data to assess the likelihood of radiation pneumonitis in lung cancer patients. Methods: This retrospective study analyzed 3-dimensional (3D) lung volume data from chest CT scans and 27 features including dosimetric, clinical, and laboratory data from 548 patients who were treated at our institution between 2010 and 2021. We developed a neural network, named MergeNet, which processes lung 3D CT, clinical, dosimetric, and laboratory data. The MergeNet integrates a convolutional neural network with subsequent fully connected layers. A support vector machine (SVM) and light gradient boosting machine (LGBM) model were also implemented for comparison. For comparison, the convolution-only neural network was implemented as well. Three-dimensional Resnet-10 network and 4-fold cross-validation were used. Results: Classification performance was quantified by using the area under the receiver operative characteristic curve (AUC) metrics. MergeNet showed the AUC of 0.689. SVM, LGBM, and convolution-only networks showed AUCs of 0.525, 0.541, and 0.550, respectively. Application of DeLong test to pairs of receiver operating characteristic curves respectively yielded P values of.001 for the MergeNet–SVM pair and 0.001 for the MergeNet–LGBM pair. Conclusion: The MergeNet model, which incorporates chest CT, clinical, dosimetric, and laboratory data, demonstrated superior performance compared to other models. However, since its prediction performance has not yet reached an efficient level for clinical application, further research is required. Contribution: This study showed that MergeNet may be an effective means to predict radiation pneumonitis. Various predictive factors can be used together for the radiation pneumonitis prediction task via the MergeNet. [ABSTRACT FROM AUTHOR]

Polyanionic materials provide a stable framework to reversibly store and release potassium (K) as a cathode for K-ion batteries. KVPO4F which operates at a 4.3 V average redox potential is one of the most energy-dense polyanionic cathodes. Although promising, its electrochemical properties show room for improvement for practical applications. In this work, we have investigated the effects of cation mixing on the electrochemical properties of KVPO4F by introducing titanium to partially substitute vanadium. While low-voltage Ti redox is a compromise from the energy density perspective, 50% Ti-substituted KVPO4F exhibits good capacity retention that compensates for the energy density decrease, delivering 98 mA h g−1 at average 4.1 V upon 50 cycles at C/5. In addition, Ti substitution can promote K diffusion by expanding K diffusion pathways, leading to improved rate capability (71 mA h g−1 at 4C). Our results suggest that judicious selection of cation compositions can be an effective approach to engineer K-ion cathode materials with a desirable electrochemical response. [ABSTRACT FROM AUTHOR]

The increasing use of photovoltaics (PVs) in distribution systems owing to the low-carbon policy has given rise to the need for various technological changes. In particular, the operation of on-load tap changers (OLTCs) has attracted attention. In traditional distribution systems, the OLTC operates via a line-drop compensator (LDC), which focuses on the load to solve the low-voltage problem; however, the problem of over-voltage caused by PVs persists. Currently, a method for operating an OLTC using the measured voltage is being researched; however, solving the voltage problem for several feeders connected to a main transformer (MT) is not viable. Therefore, this study proposes an OLTC operation method to address the feeder with the largest voltage problem depending on the direction of power flow. The proposed method selects a point where the OLTC operates using the difference between the measured and reference voltages. Setting the reference voltage can solve the problem that occurs due to the direction of power flow. Finally, the effectiveness of the proposed method is verified via case studies. Based on the results, we can conclude that the proposed method effectively solves the voltage problem, and an increase in hosting capacity can be expected. [ABSTRACT FROM AUTHOR]

Owing to the outbreak of COVID-19, researchers are exploring methods to prevent contact and non-contact infections that occur via multiple transmission routes. However, studies on preventing infections caused by droplet transmission in public transportation are insufficient. To prevent the spread of infectious diseases, a new ventilation system in railway vehicles must be developed. In this study, a novel vertical drop airflow (VDA) system is proposed to mitigate the effect of droplet transmission in a high-speed train cabin. The droplet transmission route and droplet fate are investigated using three-dimensional fluid dynamics simulations, performed employing the Eulerian–Lagrangian model. Additionally, a porous model is adopted to simulate the effect of close-fitting masks. The results indicate that 120 s after coughing, the decrease in the droplet number in the VDA system is 72.1% of that observed in the conventional system. Moreover, the VDA system effectively suppresses droplet transmission because the maximum droplet travel distances of the VDA systems are 49.9% to 67.0% of those of the conventional systems. Furthermore, the effect of reducing droplet transmission by wearing a close-fitting mask is confirmed in all systems. Thus, the decrease in both droplet number and droplet transmission area in train cabins validate that the proposed VDA system has an effective airflow design to prevent droplet infection. [ABSTRACT FROM AUTHOR]

Automatic reclosing is a typical protection method to clear temporary faults in power distribution systems. However, it has a weakness in regards to voltage sags because it produces repetitive voltage sags. In this paper, we explored the repetitive impacts of voltage sags due to the automatic reclosing of power distribution systems. The actual tests of low voltage loads were carried out for obtaining the susceptibility of voltage sags. The final results of the tests yielded the power acceptability curves of voltage sag, and the curves was transformed the 3-D Computer Business Equipment Manufacturer Association (CBEMA) format. For the quantitative evaluation of the impact of repetitive voltage sags, an assessment formulation using the voltage sag contour was proposed. The proposed formulation was tested by using the voltage sag contour data of IEEE standard and the results of the test. Through the case studies, we verified that the proposed method can be effectively used to evaluate the actual impact of repetitive voltage sags. Index Terms--Automatic reclosing, power acceptability curve, power quality, repetitive voltage sags, voltage sag contour.

This paper presents the analysis of ultrasonic signals by the partial discharge in a model transformer as well as by corona in the air at a shielded high-voltage laboratory. In addition, various noises onsite, a 345-kV substation, were measured and analyzed, for example, the vibration by core magnetostriction, cooling pump, cooling fan, onload tap changer (OLTC) operation, OLTC filtering unit operation, and air discharge pulse by corona on the transmission line. Therefore, electrical and mechanical noises onsite were removed using the proper narrow bandpass filter and the noise discrimination algorithm. Also, the developed online ultrasonic detector was applied to detect partial discharge in a 154-kV transformer with a warning level in [C.sub.2][H.sub.2] gas. As a result of an internal inspection, the source of partial discharge was found at the estimated position based on ultrasonic detection and its reliability was verified. Index Terms--Acoustic signal analysis, algorithms, bandpass filters, corona, noise, partial discharges, power transformers.

This paper presents a method to determine optimal operating strategy for distributed generation (DG) incorporating reliability worth evaluation of a distribution system. The use of DG for peak shaving could reduce the overall system operating cost and its use as standby power could reduce the customer interruption cost. If the DG operating cost is less than the utility power cost at peak time, DG should be employed to reduce the overall system operating cost. However, when customer interruption cost is also an important concern, standby power strategy for DG may be better than peak shaving. The reliability worth and the power cost evaluations are needed to determine whether DG should be operated for peak shaving or as standby power. The hourly reliability worth is incorporated in the strategy proposed in this paper to determine the optimal operating decision for the DG. Using the approach proposed in this paper, the distribution companies could determine the optimal operating strategy for their DG. Index Terms--Distributed generation (DG), distribution system, reliability worth, sequential simulation.

In the power distribution system of South Korea, the sectionalizer minimizes and recovers the system from failures, and prohibits independent operation of distributed energy resources. Therefore, it is difficult to expect reliability improvements owing to a photovoltaic system in the power distribution system. Herein, we propose a reliability-centered maintenance-scheduling method based on an economic analysis of photovoltaic integration facilities to ensure the economic feasibility of the photovoltaic system operator and the reliability of the power distribution system. Photovoltaic integration facilities are divided into two categories based on their spread of the failure, and the maintenance scheduling is evaluated according to the maximum and minimum losses according to the time of failure. Facilities that cause power outages to photovoltaics and to loads have relatively little effect on the time of failure. This is because the effects of the power outages in the loads predominate. In contrast, facilities that only cause photovoltaic outages are affected by the generation time. In particular, insulated gate bipolar transistors that operate only during photovoltaic generation have been found to be more economical for corrective replacement than preventive replacement. [ABSTRACT FROM AUTHOR]

Owing to the increasing penetration level of distributed energy resources (DER) and direct current (DC) load, the usage of low-voltage direct current (LVDC) systems has expanded to achieve efficient operations. However, because the LVDC system reaches the peak fault current at a faster rate than the alternating current (AC) system, a solution that protects the system components is necessary to maintain system integrity. It is required by the low-voltage ride-through (LVRT) that the DERs maintain their interconnections with the LVDC system and support fault recovery. In this study, a method is proposed to allow the application of the superconducting fault current limiter (SFCL) to reduce the fault current and enhance the LVRT capability. However, when the DER maintain a connection to support fault recovery, the conventional resistive-type SFCL must withstand the burden of high-temperature superconducting (HTSC) operation during fault state dependence on LVRT. Therefore, this study proposes a trigger-type SFCL to reduce the burden of the HTSC element and enhance the LVRT capability. The voltage sag related to the LVRT was improved owing to the SFCL. The proposed solution was confirmed using PSCAD/EMTDC, which is a commercial software. [ABSTRACT FROM AUTHOR]

Osteopenia and sarcopenia can cause various senile diseases and are key factors related to the quality of life in old age. There is need for portable tools and methods that can analyze osteopenia and sarcopenia risks during daily life, rather than requiring a specialized hospital setting. Gait is a suitable indicator of musculoskeletal diseases; therefore, we analyzed the gait signal obtained from an inertial-sensor-based wearable gait device as a tool to manage bone loss and muscle loss in daily life. To analyze the inertial-sensor-based gait, the inertial signal was classified into seven gait phases, and descriptive statistical parameters were obtained for each gait phase. Subsequently, explainable artificial intelligence was utilized to analyze the contribution and importance of descriptive statistical parameters on osteopenia and sarcopenia. It was found that XGBoost yielded a high accuracy of 88.69% for osteopenia, whereas the random forest approach showed a high accuracy of 93.75% for sarcopenia. Transfer learning with a ResNet backbone exhibited appropriate performance but showed lower accuracy than the descriptive statistical parameter-based identification result. The proposed gait analysis method confirmed high classification accuracy and the statistical significance of gait factors that can be used for osteopenia and sarcopenia management. [ABSTRACT FROM AUTHOR]