MFI ZEOLITE MEMBRANES ON CERAMIC HOLLOW FIBERS: SCALABLE FABRICATION PROCESSES AND HYDROCARBON SEPARATION PROPERTIES

MFI zeolite membranes are attractive for the separation of industrially important hydrocarbon gas mixtures such as xylene isomers, butane isomers and natural gas components, based on the differences in the chemical and physical properties. However, zeolite membranes including MFI membranes have been unsuccessful in achieving economic viability for industrial-scale gas separation applications. The large-scale industrial application of zeolite membrane systems can be realized by overcoming the following barriers: firstly, develop scalable and reliable membrane fabrication strategies to produce the high-performance membrane; secondly, reduce the cost and achieve performance intensification of the membrane system by employing hollow fiber modules with high membrane area per unit volume; and thirdly, obtain a thorough understanding of multicomponent separation behavior in zeolite membranes at industrially interesting conditions. In the above context, the overall focus of this thesis is to develop novel, technologically scalable fabrication strategies to make thin and highly selective MFI zeolite membranes and to understand their synthesis-structure-permeation property relations by a combination of experiment and modeling. This thesis has focused on the MFI zeolite type, because of its particularly attractive properties for a wide range of hydrocarbon separations.Ph.D

A Survey on Awesome Korean NLP Datasets

English based datasets are commonly available from Kaggle, GitHub, or recently published papers. Although benchmark tests with English datasets are sufficient to show off the performances of new models and methods, still a researcher need to train and validate the models on Korean based datasets to produce a technology or product, suitable for Korean processing. This paper introduces 15 popular Korean based NLP datasets with summarized details such as volume, license, repositories, and other research results inspired by the datasets. Also, I provide high-resolution instructions with sample or statistics of datasets. The main characteristics of datasets are presented on a single table to provide a rapid summarization of datasets for researchers.Comment: 11 pages, 1 horizontal page for large tabl

Korean parents\u27 attitudes, motivations, and home literacy practices toward bilingualism between Korean and English in Korea

The purpose of the study is to examine Korean parents’ attitudes, motivations, and home literacy practices toward their children’s participation in bilingualism in Korean and English in Korea. The success of foreign language learning is influenced by positive attitudes and the level of motivation regarding the target language. Language learners’ attitudes and motivations toward a target language are closely related to their development of language proficiency, and children are often strongly influenced by their parents. The present study was conducted by the survey that was comprised of four-part Likert-type statements. The participants consisted of parents who have children enrolled in the elementary school located in the center of Korea. Parents of 218 responded to the survey questionnaires on December 2011. For the research questions, a two-way analysis of variance was applied based on the parents’ demographic information, and a multiple regression in the methods was used to examine the correlations among attitudes, motivations, and home literacy practices. The results of this research indicate that most participants had highly favorable attitudes toward bilingualism based on the scores according to both holistic view and fragmented view. Although there was slightly a difference between the two views, the parents’ attitudes toward the holistic view of bilingualism were more favorable than those toward the fragmented view. Also, the parents showed favorable responses to all five motivations toward bilingualism. While the scores for the integrative motivation were the highest, on the other hand, those for the attributions about past failure were the lowest. In terms of home literacy practices, the parents’ responses were positive for all the practices. The formal practices were the preferred activity for children’s bilingualism, whereas the favorableness to CALL practices was the lowest. Attitudes and motivations can influence each other without a hierarchy. The parents’ attitudes, motivations, and home literacy practices toward bilingualism were measured based on the demographic information such as gender, age, socio-economic status, etc, resulting in a variety of significant findings. Also, attitudes and motivations allow us to predict the favorableness of home literacy practices. The present study proposes some recommendations to policy makers and concludes with several suggestions for further research

Mixed Reality Interface for Digital Twin of Plant Factory

An easier and intuitive interface architecture is necessary for digital twin of plant factory. I suggest an immersive and interactive mixed reality interface for digital twin models of smart farming, for remote work rather than simulation of components. The environment is constructed with UI display and a streaming background scene, which is a real time scene taken from camera device located in the plant factory, processed with deformable neural radiance fields. User can monitor and control the remote plant factory facilities with HMD or 2D display based mixed reality environment. This paper also introduces detailed concept and describes the system architecture to implement suggested mixed reality interface.Comment: 5 pages, 7 figure

Analysis on English Vocabulary Appearance Pattern in Korean CSAT

A text-mining-based word class categorization method and LSTM-based vocabulary pattern prediction method are introduced in this paper. A preprocessing method based on simple text appearance frequency analysis is first described. This method was developed as a data screening tool but showed 4.35 ~ 6.21 times higher than previous works. An LSTM deep learning method is also suggested for vocabulary appearance pattern prediction method. AI performs a regression with various size of data window of previous exams to predict the probabilities of word appearance in the next exam. Predicted values of AI over various data windows are processed into a single score as a weighted sum, which we call an "AI-Score", which represents the probability of word appearance in next year's exam. Suggested method showed 100% accuracy at the range 100-score area and showed only 1.7% error of prediction in the section where the scores were over 60 points. All source codes are freely available at the authors' Git Hub repository. (https://github.com/needleworm/bigdata_voca)Comment: update additional experiment resul

CongNaMul: A Dataset for Advanced Image Processing of Soybean Sprouts

We present 'CongNaMul', a comprehensive dataset designed for various tasks in soybean sprouts image analysis. The CongNaMul dataset is curated to facilitate tasks such as image classification, semantic segmentation, decomposition, and measurement of length and weight. The classification task provides four classes to determine the quality of soybean sprouts: normal, broken, spotted, and broken and spotted, for the development of AI-aided automatic quality inspection technology. For semantic segmentation, images with varying complexity, from single sprout images to images with multiple sprouts, along with human-labelled mask images, are included. The label has 4 different classes: background, head, body, tail. The dataset also provides images and masks for the image decomposition task, including two separate sprout images and their combined form. Lastly, 5 physical features of sprouts (head length, body length, body thickness, tail length, weight) are provided for image-based measurement tasks. This dataset is expected to be a valuable resource for a wide range of research and applications in the advanced analysis of images of soybean sprouts. Also, we hope that this dataset can assist researchers studying classification, semantic segmentation, decomposition, and physical feature measurement in other industrial fields, in evaluating their models. The dataset is available at the authors' repository. (https://bhban.kr/data)Comment: Accepted to International Conference on ICT Convergence 202

Toll-like receptor 2 contributes to chemokine gene expression and macrophage infiltration in the dorsal root ganglia after peripheral nerve injury

<p>Abstract</p> <p>Background</p> <p>We have previously reported that nerve injury-induced neuropathic pain is attenuated in toll-like receptor 2 (TLR2) knock-out mice. In these mice, inflammatory gene expression and spinal cord microglia actvation is compromised, whereas the effects in the dorsal root ganglia (DRG) have not been tested. In this study, we investigated the role of TLR2 in inflammatory responses in the DRG after peripheral nerve injury.</p> <p>Results</p> <p>L5 spinal nerve transection injury induced the expression of macrophage-attracting chemokines such as CCL2/MCP-1 and CCL3/MIP-1 and subsequent macrophage infiltration in the DRG of wild-type mice. In TLR2 knock-out mice, however, the induction of chemokine expression and macrophage infiltration following nerve injury were markedly reduced. Similarly, the induction of IL-1β and TNF-α expression in the DRG by spinal nerve injury was ameliorated in TLR2 knock-out mice. The reduced inflammatory response in the DRG was accompanied by attenuation of nerve injury-induced spontaneous pain hypersensitivity in TLR2 knock-out mice.</p> <p>Conclusions</p> <p>Our data show that TLR2 contributes to nerve injury-induced proinflammatory chemokine/cytokine gene expression and macrophage infiltration in the DRG, which may have relevance in the reduced pain hypersensitivity in TLR2 knock-out mice after spinal nerve injury.</p

Effect of Doppler shift on adaptive OFDM modulation for cognitive radio application

In this thesis, the effect of Doppler shift on adaptive orthogonal frequency-division multiplex (OFDM) modulation in a cognitive radio (CR) application is investigated. We present Monte Carlo simulations of OFDM modulation in which a group or groups of subcarriers are modulated using quadrature phase-shift keying (QPSK) modulation and 16-ary quadrature amplitude modulations (16QAM). We show that turning off some subcarriers does not affect the performance as long as the effective Eb/No remains the same. We also present Monte Carlo simulations where the power ratio of two sets of subcarriers is changed while maintaining the same total power in order to investigate the effect on performance. Finally, we consider a two-user CR scenario and investigate the performance effect on a primary user by a secondary user in terms of various Doppler shift offsets where both the primary user and secondary user use OFDM modulations.http://archive.org/details/effectofdopplers1094548119Lieutenant, Republic of Korea NavyApproved for public release; distribution is unlimited