• Educational Technology International
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• v.25 no.2
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• pp.231-260
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• 2024

This study suggests that educational recommender systems should be explainable and extend beyond the commercially driven algorithms that primarily rely on user preferences and purchase behaviors. Instead, we propose a recommendation method that considers how and why people learn by employing the relative importance of various learner variables. To develop a recommendation algorithm, 100 adult participants used 4 to 6 foreign language learning mobile applications(apps), generating a dataset of 557 user perception reports. Using this data, we designed and developed a recommender system based on the importance weights of 14 learner variables, categorized into four groups: (a) demographic information, (b) motivational orientation for language learning (instrumental vs. integrative), (c) learning styles, and (d) learning experience. The results based on RandomForestRegressor model revealed that language learning motivation, learning styles (specifically information processing), and usage frequency were significantly more influential than general demographic factors in predicting learners' evaluation of the apps. Furthermore, learners' perception of the recommender system revealed that the recommender system was relevant and engaging, effectively meeting their needs and assisting them in selecting appropriate language learning apps. Overall, this study demonstrates the potential of educational recommender systems that consider learners' motivation, experience, and learning styles.

• Journal of the Society of Disaster Information
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• v.15 no.4
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• pp.548-559
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• 2019

Purpose: Analysis method of V2I data driven motorway service area usage behavior to cope with manpower survey. Method: Segmentation of traveling state group and boundary using the distribution characteristics of traveling speed data of individual vehicles. Result: As a result of the verification, the use rate of resting places in lunchtime surged, and the boundary between the distribution status of the traffic speed data was clearly or unclear. Conclusion: The effect of the cost reduction is big because it can cope with the use of rest area survey by manpower and there is no limit in the time and space range of investigation. The dynamic utilization rate of each time sequence, such as a service area/drowsiness shelter/simple service area, with a V2I system, can be calculated. Identify illegal parking on highway section. Identify the unexpected situation in the road section. Identify the real-time service area utilization rate and congestion information.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.1_2
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• pp.125-134
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• 2004

Recently, an on-chip compressed cache system was presented to alleviate the processor-memory Performance gap by reducing on-chip cache miss rate and expanding memory bandwidth. This research Presents an extended on-chip compressed cache system which also significantly expands main memory capacity. Several techniques are attempted to expand main memory capacity, on-chip cache capacity, and memory bandwidth as well as reduce decompression time and metadata size. To evaluate the performance of our proposed system over existing systems, we use execution-driven simulation method by modifying a superscalar microprocessor simulator. Our experimental methodology has higher accuracy than previous trace-driven simulation method. The simulation results show that our proposed system reduces execution time by 4-23% compared with conventional memory system without considering the benefits obtained from main memory expansion. The expansion rates of data and code areas of main memory are 57-120% and 27-36%, respectively.

• Spatial Information Research
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• v.9 no.1
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• pp.73-89
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• 2001

In the recent rapidly changing technology environment the computerization of administration business using GIS is driven or will be driven to give improved information services for the people by local government or central government with huge budget. Development of GIS for local governments is investigated with huge budge. Development of GIS for local governments is investigated to prevent local government from investing redundant money and to reuse the existing investment at this time. The purpose of this study is finding the development method of Land Management Information System (LMIS) to give service and share data in various computing environment of local governments. To do this, we have to develop LMIS as open system with interoperability and we explain it with a focus to framework of Open LMIS. According to recent trend of technology we developed Open LMIS for convenient maintenance with nationwide LMIS expansion at hand. This system was developed at the $\ulcorner$Land Management Information System Development$\lrcorner$project which was managed by Ministry of Construction and Transportation (MOCT). GIS application was based on OpenGIS CORBA specification for development of standard interface and RUP(Rational Unified Process) for development method and LML(Unified Modeling Language) for system design. Developed systems were land administration system for local government, spatial planning support system for regional government, and land policy support system for MOCT.

• Journal of Korea Water Resources Association
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• v.50 no.8
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• pp.521-535
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• 2017

Acoustic Doppler Current Profilers (ADCPs) have been widely utilized for assessing streamflow discharge, yet few comprehensive studies were conducted to evaluate discharge uncertainty in consideration of individual uncertainty components. It could be mostly because it was not easy to determine which uncertainty framework can be appropriate to rigorously analyze streamflow discharge driven by ADCPs. In this regard, considerable efforts have been made by scientific and engineering societies to develop a standardized theoretical framework for uncertainty analysis in hydrometry. One of the well-established UA methodology based on sound statistical and engineering concepts is Guide to the Expression of Uncertainty Measurement (GUM) adopted widely by various scientific and research communities. This research fundamentally adapted the GUM framework to assess individual uncertainty components of ADCP discharge measurements, and subsequently provided results of a customized experiment in a controllable real-scale artificial river channel. We focused particularly upon sensitivities of uncertainty components in the GUM framework driven by ADCPs direct measurements such as depths, edge distance, submerged depth, velocity gap, sampling time, repeatability, bed roughness and so on. Section-by-Section method for ADCP discharge measurement was applied for uncertainty analysis for this study. All of measurements were carefully compared with data using other instrumentations such as ADV to evaluate individual uncertainty components.

• Coupled systems mechanics
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• v.8 no.1
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• pp.71-93
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• 2019

Finite element simulations of solid mechanics problems often involve the use of Non-Confirming Meshes (NCM) to increase accuracy in capturing nonlinear behavior, including damage and plasticity, in part of a solid domain without an undue increase in computational costs. In the presence of material nonlinearity and plasticity, higher-order variables are often needed to capture nonlinear behavior and material history on non-conforming interfaces. The most popular formulations for coupling non-conforming meshes are dual methods that involve the interpolation of a traction field on the interface. These methods are subject to the Ladyzhenskaya-Babuska-Brezzi (LBB) stability condition, and are therefore limited in their implementation with the higher-order elements needed to capture nonlinear material behavior. Alternatively, the enriched discontinuous Galerkin approach (EDGA) (Haikal and Hjelmstad 2010) is a primal method that provides higher order kinematic fields on the interface, and in which interface tractions are computed from local finite element estimates, therefore facilitating its implementation with nonlinear material models. The inclusion of higher-order interface variables, however, presents the issue of preserving material history at integration points when a increase in integration order is needed. In this study, the enriched discontinuous Galerkin approach (EDGA) is extended to the case of small-deformation plasticity. An interface-driven Gauss-Kronrod integration rule is proposed to enable adaptive enrichment on the interface while preserving history-dependent material data at existing integration points. The method is implemented using classical J2 plasticity theory as well as the pressure-dependent Drucker-Prager material model. We show that an efficient treatment of interface variables can improve algorithmic performance and provide a consistent approach for coupling non-conforming meshes in inelasticity.

• Journal of the Korean Geotechnical Society
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• v.25 no.6
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• pp.47-57
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• 2009

In this study, the ultimate lateral load capacity of pile driven into multi-layered soil was estimated using cone penetration test results and a method was proposed to reflect multi-layered soil conditions. For multi-layered specimens prepared with different relative density at different layers, the cone penetration tests and lateral pile load tests were conducted. Based on the test results, measured and estimated values of the ultimate lateral load were compared and analyzed. The estimated results were obtained from the methods proposed by Broms (1964), Petrasovits & Award (1972) and Prasad & Chari (1999). The method was proposed for modifying the earth pressure distribution of Prasad & Chari (1999) to consider multi-layered soil conditions. From the analysis, it was seen that results obtained from the proposed method showed improvement with less data scatter similarly to those obtained from Broms (1964) and Petrasovits & Award (1972)'s methods.

• Nuclear Engineering and Technology
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• v.56 no.8
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• pp.2948-2957
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• 2024

High-order harmonic techniques can be used to recreate neutron flux distributions in reactor cores using the neutron diffusion equation. However, traditional source iteration and source correction iteration techniques have sluggish convergence rates and protracted calculation periods. The correctness of the implicitly restarted Arnoldi method (IRAM) in resolving the eigenvalue problems of the one-dimensional and two-dimensional neutron diffusion equations was confirmed by computing the benchmark problems SLAB_1D_1G and two-dimensional steady-state TWIGL using IRAM. By integrating Galerkin projection with Proper Orthogonal Decomposition (POD) techniques, a POD-Galerkin reduced-order model was developed and the IRAM model was used as the full-order model. For 14 macroscopic cross-section values, the TWIGL benchmark problem was perturbed within a 20% range. We extracted 100 sample points using the Latin hypercube sampling method, and 70% of the samples were used as the testing set to assess the performance of the reduced-order model The remaining 30% were utilized as the training set to develop the reduced-order model, which was employed to rebuild the TWIGL benchmark problem. The reduced-order model demonstrates good flexibility and can efficiently and accurately forecast the effective multiplication factor and neutron flux distribution in the core. The reduced-order model predicts k_eff and neutron flux distribution with a high degree of agreement compared to the full-order model. Additionally, the reduced-order model's computation time is only 10.18% of that required by the full-order model.The neutron flux distribution of the steady-state TWIGL benchmark was recreated using the reduced-order model. The obtained results indicate that the reduced-order model can accurately predict the k_eff and neutron flux distribution of the steady-state TWIGL benchmark.Overall, the proposed technique not only has the potential to accurately project neutron flux distributions in transient settings, but is also relevant for reconstructing neutron flux distributions in steady-state conditions; thus, its applicability is bound to increase in the future.

• Journal of Korea Water Resources Association
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• v.56 no.10
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• pp.631-639
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• 2023

Flash drought (FD), characterized by the rapid onset and intensification, can significantly impact ecosystems and induce immediate water stress. A more comprehensive understanding of the causes and characteristics of FD events is required to enhance drought monitoring. Therefore, we investigated the FD events took place over the Korean peninsula using Global Land Data Assimilation System (GLDAS) data from 2012 to 2022. We first detected FD events using the stress-based method (Standardized Evaporative Stress Ratio, SESR), and analyzed the frequency and duration of FDs. The FD events were classified into three cases based on the variations in Actual Evapotranspiration (AET) and potential Evapotranspiration (PET), and spatially analyzed. Results revealed that there are regional disparities in frequency and duration of FDs, with a mean frequency of 6.4 and duration of 31 days. When classified into Case 1 (normal condition), Case 2 (AET-driven), and Case 3 (PET-driven), we found that Case 2 FDs emerged approximately 1.5 times more frequently than those driven by PET (Case 3) across the Korean peninsula. Case 2 FDs were found to be induced under water-limited conditions, and led both AET and PET to be decreased. Conversely, Case 3 FDs occurred under energy-limited conditions, with increase in both. Case 2 FDs predominantly affected the northwestern and central-southern agricultural regions, while Case 3 occurred in the eastern region, characterized by forested land cover. These findings offers insights into our understanding of FDs over the Korean peninsula, considering climate factors, land cover, and water availability.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.209-223
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• 2024

In the context of the fourth industrial revolution, data-driven decision-making has increasingly become pivotal. However, the integrity of data analysis is compromised if data quality is not adequately ensured, potentially leading to biased interpretations. This is particularly critical for water level data, essential for water resource management, which often encounters quality issues such as missing values, spikes, and noise. This study addresses the challenge of noise-induced data quality deterioration, which complicates trend analysis and may produce anomalous outliers. To mitigate this issue, we propose a noise removal strategy employing Wavelet Transform, a technique renowned for its efficacy in signal processing and noise elimination. The advantage of Wavelet Transform lies in its operational efficiency - it reduces both time and costs as it obviates the need for acquiring the true values of collected data. This study conducted a comparative performance evaluation between our Wavelet Transform-based approach and the Denoising Autoencoder, a prominent machine learning method for noise reduction.. The findings demonstrate that the Coiflets wavelet function outperforms the Denoising Autoencoder across various metrics, including Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and Mean Squared Error (MSE). The superiority of the Coiflets function suggests that selecting an appropriate wavelet function tailored to the specific application environment can effectively address data quality issues caused by noise. This study underscores the potential of Wavelet Transform as a robust tool for enhancing the quality of water level data, thereby contributing to the reliability of water resource management decisions.