• Transactions of the Korean Society of Automotive Engineers
• /
• v.25 no.3
• /
• pp.380-388
• /
• 2017

Wood pyrolysis oil(WPO) has been regarded as an alternative fuel for diesel engines. However, WPO is not feasible for use directly in diesel engines due to its poor fuel quality such as low energy density, high acidity, high viscosity and low cetane number. The most widely used approach to improve WPO fuel quality is to blend WPO with other hydrocarbon fuels that have a higher cetane number. However, WPO and fossil fuels are not usually blended because of their different polarity. Also, clogging and polymerization problems in the fuel supply system can occur when the engine is operated with WPO. Polymerization can be prevented by diluting WPO with other alcohol fuels. However, WPO-alcohol blended fuel does not produce self-ignition. Therefore, additional cetane enhancement to the blended fuel is required to enhance auto-ignitability. In this study, WPO was blended with n-butanol and two cetane enhancements(PEG 400 and 2-EHN) for application to a diesel generator. Experimental results showed that the WPO-butanol blended fuel achieved a very stable engine operation under maximum WPO content of 20 wt%.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.38 no.4
• /
• pp.371-377
• /
• 2014

In tissue engineering, a scaffold is a three-dimensional(3D) structure that serves as a template for regeneration the functions of damaged tissues or organs. Among materials for scaffolds, polycaprolactone(PCL) and ${\beta}$-tricalcium phosphate(${\beta}$-TCP) are biodegradable and biocompatible. In this study, we fabricated 3D PCL, blended PCL (60 wt %)/${\beta}$-TCP (40 wt %), and pure ${\beta}$-TCP scaffolds by a multi-head scaffold fabrication system. Scaffolds with a pore size of $600{\pm}20{\mu}m$ was observed by scanning electron microscopy. The effects of 3D PCL, blended PCL (60 wt %)/${\beta}$-TCP (40 wt %) and pure ${\beta}$-TCP scaffolds were analyzed by evaluating their mechanical characteristics. In addition, in an in-vitro study using osteoblast-like saos-2 cells, we confirmed the effects of 3D scaffolds on cellular behaviors such as cell adhesion and proliferation. In summary, the 3D blended PCL (60 wt %)/${\beta}$-TCP (40 wt %) scaffold was found to be suitable for human cancellous bone in terms of its the compressive strength, biocompatibility, and osteoconductivity. Thus, blending PCL and ${\beta}$-TCP could be a promising approach for fabricating 3D scaffolds for effective bone regeneration.

• Computers and Concrete
• /
• v.20 no.2
• /
• pp.247-255
• /
• 2017

This study aimed to develop a Rule Based Mamdani Type Fuzzy Logic (RBMFL) model to predict the flexural strengths and compressive strengths of blended cements under elevated temperatures. Clinoptilolite was used as cement substitution material in the experimental stage. Substitution ratios in the cement mortar mix designs were selected as 0% (reference), 5%, 10%, 15% and 20%. The data used in the modeling process were obtained experimentally, after mortar specimens having reached the age of 90 days and exposed to $300^{\circ}C$, $400^{\circ}C$, $500^{\circ}C$ temperatures for 3 hours. In the RBMFL model, temperature ($C^{\circ}$) and substitution ratio of clinoptilolite (%) were inputs while the compressive strengths and flexural strengths of mortars were outputs. Results were compared by using some statistical methods. Statistical comparison results showed that rule based Mamdani type fuzzy logic can be an alternative approach for the evaluation of the mechanical properties of concrete under elevated temperature.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.13 no.4
• /
• pp.221-230
• /
• 2017

BL(Blended Learning) has been presented as a promising alternative learning approach. BL is defined as a learning approach that combines e-learning and face-to-face classroom learning. The adoption of BL in computer practice class is necessary due to the characteristics of computer practice class itself. This study proposes a research model that examines the determinants of learner's satisfaction of computer practice classes in BL environment. Considering the characteristics of computer practices classes contents and instructor interaction were identified as the determinants. The research model is tested using a questionnaire survey of 141 participants. Confirmatory factor analysis (CFA) was performed to test the reliability and validity of the measurements. The partial least squares (PLS) method was used to validate the measurement and hypotheses. The empirical findings shows that contents easiness and contents constructs are the primary determinants of instructor interaction in BL. Instructor interaction was also found to be related to the learner's satisfaction resulting in re-using. The findings provide insight into the planning and utilizing BL in computer practice classes to enhance learner's satisfaction.

• Journal of Industrial Convergence
• /
• v.21 no.8
• /
• pp.1-12
• /
• 2023

The purpose of the study is to analyze the impact of blended learning's external classroom formats and internal teaching strategies, which has been implemented in university classes due to COVID-19, on students' academic achievement and learners' perceptions, as well as to provide insights into the desirable direction of online education. The study was conducted during the 1st semester of 2022 at G University, targeting students taking Calculus I. The experimental group consisted of 117 students, while the control group consisted of 707 students. Blended learning, involving a combination of face-to-face classes, online classes, and mixed teaching methods, was implemented, and academic achievement and learner perceptions were assessed. The research findings indicate that compared to solely online classes, adopting a blended learning approach with online classes before the midterm and face-to-face classes afterwards resulted in a decline in academic achievement. The unprepared and simplistic external format of blended learning was found to be ineffective, however, a blended learning model consisting solely of online classes, incorporating a mix of asynchronous and synchronous instruction, demonstrated positive learner perceptions. Additionally, utilizing technology in the teaching strategies yielded positive outcome.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.8
• /
• pp.3473-3487
• /
• 2020

In this paper, we present a new approach to creating speech animation with emotional expressions using a small set of example models. To generate realistic facial animation, two example models called key visemes and expressions are used for lip-synchronization and facial expressions, respectively. The key visemes represent lip shapes of phonemes such as vowels and consonants while the key expressions represent basic emotions of a face. Our approach utilizes a text-to-speech (TTS) system to create a phonetic transcript for the speech animation. Based on a phonetic transcript, a sequence of speech animation is synthesized by interpolating the corresponding sequence of key visemes. Using an input parameter vector, the key expressions are blended by a method of scattered data interpolation. During the synthesizing process, an importance-based scheme is introduced to combine both lip-synchronization and facial expressions into one animation sequence in real time (over 120Hz). The proposed approach can be applied to diverse types of digital content and applications that use facial animation with high accuracy (over 90%) in speech recognition.

• The Journal of the Convergence on Culture Technology
• /
• v.8 no.1
• /
• pp.239-244
• /
• 2022

Neural Machine Translation (NMT) is gradually breaking down the boundary between human and machine translation. We look at actual cases of human and machine translation and discuss why machine translation needs a human touch. In this paper, we raise three driving questions: Can humans be replaced by machines?; How human translators can remain successful in a NMT-driven world?; Is it possible to eliminate language barrier in the era of NMT and World Englishes? The answers to these questions are all negative. We suggest that machine translation is a useful tool with rapidity, accuracy, and low cost productivity. However, the machine translation is limited in the areas of culture, borrowing, ambiguity, new words and (national) dialects. The machines cannot imitate the emotional and intellectual abilities of human translators since machines are based on machine learning, while humans are on intuition. The machine translation will be a useful tool that does not cause moral problems when using methods such as back translation and human post-editing. To conclude, we propose the blended approach that machine translation cannot be completed without the touch of human translation.

• Nuclear Engineering and Technology
• /
• v.55 no.6
• /
• pp.1988-1993
• /
• 2023

This experimental study investigated the effect of silica fume mixed in concrete blocks on laser-induced explosion behavior. We used a 5.3 kW fiber laser as a thermal source to induce explosive spalling on a concrete surface blended with and without silica fume. An analytical approach based on the difference in the removal rate and thermal behavior was used to determine the effect of silica fume on laser-induced explosive spalling. A scanner was employed to calculate the laser-scabbled volume of the concrete surface to derive the removal rate. The removal rate of the concrete mixed with silica fume was higher than that of without silica fume. Thermal images acquired during scabbling were used to qualitatively analyze the thermal response of laser-induced explosive spalling on the concrete surface. At the early stage of laser heating, an uneven spatial distribution of surface temperature appeared on the concrete blended with silica fume because of frequent explosive spalling within a small area. By contrast, the spalling frequency was relatively lower in laser-heated concrete without silica fume. Furthermore, we observed that a larger area was removed via a single explosive spalling event owing to its high porosity.

• Nuclear Engineering and Technology
• /
• v.55 no.8
• /
• pp.2854-2863
• /
• 2023

Objective: To present a hybrid approach that incorporates a constrained beam-hardening estimator (CBHE) and deep learning (DL)-based post-refinement for metal artifact reduction in dental cone-beam computed tomography (CBCT). Methods: Constrained beam-hardening estimator (CBHE) is derived from a polychromatic X-ray attenuation model with respect to X-ray transmission length, which calculates associated parameters numerically. Deep-learning-based post-refinement with an artifact disentanglement network (ADN) is performed to mitigate the remaining dark shading regions around a metal. Artifact disentanglement network (ADN) supports an unsupervised learning approach, in which no paired CBCT images are required. The network consists of an encoder that separates artifacts and content and a decoder for the content. Additionally, ADN with data normalization replaces metal regions with values from bone or soft tissue regions. Finally, the metal regions obtained from the CBHE are blended into reconstructed images. The proposed approach is systematically assessed using a dental phantom with two types of metal objects for qualitative and quantitative comparisons. Results: The proposed hybrid scheme provides improved image quality in areas surrounding the metal while preserving native structures. Conclusion: This study may significantly improve the detection of areas of interest in many dentomaxillofacial applications.

• Structural Engineering and Mechanics
• /
• v.74 no.1
• /
• pp.55-67
• /
• 2020

The common practice to predict the characteristic structural load effects (LEs) in long reference periods is to employ the extreme value theory (EVT) for building limit distributions. However, most applications ignore that LEs are driven by multiple loading events and thus do not have the identical distribution, a prerequisite for EVT. In this study, we propose the composite extreme value modeling approach using clustering to (a) cluster initial blended samples into finite identical distributed subsamples using the finite mixture model, expectation-maximization algorithm, and the Akaike information criterion; (b) combine limit distributions of subsamples into a composite prediction equation using the generalized Pareto distribution based on a joint threshold. The proposed approach was validated both through numerical examples with known solutions and engineering applications of bridge traffic LEs on a long-span bridge. The results indicate that a joint threshold largely benefits the composite extreme value modeling, many appropriate tail approaching models can be used, and the equation form is simply the sum of the weighted models. In numerical examples, the proposed approach using clustering generated accurate extrema prediction of any reference period compared with the known solutions, whereas the common practice of employing EVT without clustering on the mixture data showed large deviations. Real-world bridge traffic LEs are driven by multi-events and present multipeak distributions, and the proposed approach is more capable of capturing the tendency of tailed LEs than the conventional approach. The proposed approach is expected to have wide applications to general problems such as samples that are driven by multiple events and that do not have the identical distribution.