김희웅 교수

The mean absolute percentage error (MAPE) is one of the most widely used measures of forecast accuracy, due to its advantages of scale-independency and interpretability. However, MAPE has the significant disadvantage that it produces infinite or undefined values for zero or close-to-zero actual values. In order to address this issue in MAPE, we propose a new measure of forecast accuracy called the mean arctangent absolute percentage error (MAAPE). MAAPE has been developed through looking at MAPE

In semiconductor manufacturing, a wafer bin map (WBM) is a map that consists of assigned bin values for dies based on wafer test results (e.g., value 1 for good dies and value 0 for defective dies). The bin values of adjacent dies are often spatially correlated, forming some systematic defect patterns. These non-random defect patterns occur due to assignable causes; therefore, it is important to identify these systematic defect patterns in order to know the root causes of failure and to take act

The objective of this study is to express the four types of personality of a robot based on Myers-Briggs Type Indicator by controlling the size, speed, and frequency of the gestures of a robot and to examine userpsila impressions of the robot by controlling the gesture design factors. The independent variables were three gesture design factors (speed, velocity, and frequency) with two levels each, producing eight gesture types. The eight gesture types were presented in two robot positions, a spe

In ocean transportation, detecting vessel delays in advance or in real time is important for fourth-party logistics (4PL) in order to fulfill the expectations of customers and to help customers reduce delay costs. However, the early detection of vessel delays faces the challenges of numerous uncertainties, including weather conditions, port congestion, booking issues, and route selection. Recently, 4PLs have adopted advanced tracking technologies such as satellite-based automatic identification

Purpose: This study was conducted to design and implement a fundamental nursing practice based on flipped learning and to examine the effects. Methods: Participants were 57 students who were taking the fundamental nursing practice course at D university in N city. The study included processes of instructional design, action/effects and reflection. Data were analyzed using paired t-test with the SPSS/WIN 23.0. Results: In the instructional design stage, the class consisted of 3 parts: outside cla

Plasmonic photoelectrochemical (PEC) water splitting has excited immense interest, as it can overcome the intrinsic limitations of semiconductors, in terms of light absorption, by the localized-surface plasmon resonances effect. Here, to get insight into the role of plasmonic hot carriers in plasmonic water splitting, a rational design of an antenna-reactor type Pt/Ag/TiO₂ metal-semiconductor Schottky nanodiode was fabricated and used as a photoanode. Using the designed PEC cell syste

This study considers the binary classification of functional data collected in the form of curves. In particular, we assume a situation in which the curves are highly mixed over the entire domain, so that the global discriminant analysis based on the entire domain is not effective. This study proposes an interval-based classification method for functional data: the informative intervals for classification are selected and used for separating the curves into two classes. The proposed method, call

Latent class models have been widely used in longitudinal studies to uncover unobserved heterogeneity in a population and find the characteristics of the latent classes simultaneously using the class allocation probabilities dependent on predictors. However, previous latent class models for longitudinal data suffer from uncertainty in the choice of the number of latent classes. In this study, we propose a Bayesian nonparametric latent class model for longitudinal data, which allows the number of

In semiconductor manufacturing, the package test is a process that verifies whether the product specifications are satisfied before the semiconductor products are finally shipped to customers. The packaged chips are classified as good or defective according to the verification results. To ensure high-quality products and customer satisfaction, it is important to detect defective chips during the package test. In this article, we consider the problem of predicting potential defects in advance usi

We explore distance dependent variation of the coherence length relevant to DNA charge-transfer processes within 5'-GAnG3-3' DNA sequences. Recently developed on-the-fly filtered propagator functional path integral approach was employed to sort out transport trajectories with significant contribution and to analyze correlation between electronic states. In particular, the coherence length was quantitatively determined through characteristics of off-diagonal quantum trajectories. Simulated cohere

The spatially varying coefficient process model is a nonstationary approach to explaining spatial heterogen-eity by allowing coefficients to vary across space. In this article, we develop a methodology for generalizing this model to accommodate geographically hierarchical data. This article considers two-level hierarchical structures and allow for the coefficients of both low-level and high-level units to vary over space. We assume that the spatially varying low-level coefficients follow the mul

Deep generative models have demonstrated an excellent ability to generate data by learning their distribution. Despite their unsupervised nature, these models can be implemented in semi-supervised learning scenarios by treating the class labels as additional latent variables. In this article, we propose a deep generative model for semi-supervised learning that offsets label noise, which is a ubiquitous feature in large-scale datasets owing to the high cost of annotation. We assume that noisy lab

The Taguchi robust design method traditionally deals with single‐characteristic problems. Various methods have been developed for extending the Taguchi single‐characteristic robust design method to the case of multi‐characteristic robust design problems. However, most of those methods have shortcomings in that they do not properly consider the variance–covariance structures among performance characteristics and/or do not preserve the original properties of the Taguchi signal‐to‐noise ratio for s

Identifying the charge transfer at metal-semiconductor interfaces by detecting hot electrons is crucial for understanding the mechanism of catalytic reactions and the development of an engineered catalyst structure. Over the last two decades, the development of catalytic nanodiodes has enabled us to directly measure chemically induced hot electron flux and relate it to catalytic activity. A crucial question is the role of interfacial sites at metal-oxide interfaces in determining catalytic activ