• Journal of Astronomy and Space Sciences
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• 제29권2호
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• pp.191-194
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• 2012

The observed distribution of a blending-corrected sample of Einstein ring crossing times, $t_E$, for microlensing events toward the galactic bulge/bar are analyzed. An inspection of the distribution of crossing times suggests that it may be bimodal, indicating that two populations of lenses could be responsible for observed microlensing events. Given the possibility that microlensing in this direction can be due to the two most common classes of stars, main-sequence and white dwarf, we analyze and show via Monte Carlo simulations that the observed bimodality of $t_E$ can be derived from their accepted mass functions, and the density distributions of both stellar populations in the galactic disk and bulge/bar, with a transverse velocity distribution that is consistent with the density distribution. Kolmogorov-Smirnov (KS) one sample tests shows that a white dwarf population of about 25% of all stars in the galaxy agrees well with the observed bimodality with a KS significance level greater than 97%. This is an expanded and updated version of a previous investigation (Wickramasinghe, Neusima, & Struble, in Mao 2008). A power-point version of the talk, with introductory figures, is found at: https://sites.google.com/site/rhkochconference/agenda-1/program.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2018년도 학술발표회
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• pp.410-410
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• 2018

Evaporative Demand Drought Index (EDDI)는 미국해양대기관리처 (National Oceanic and Atmospheric Administration, NOAA)에서 2016년에 개발한 가뭄지표로, 기존의 가뭄지표가 주로 강수량과 기온에 초점을 두고 가뭄을 판단하는 반면 토양의 수분 스트레스의 신호를 바탕으로 증발산수요의 상대적인 변화를 계산하여 가뭄지표에 대한 조기 경보를 제공한다. EDDI는 강수량을 이용한 기존의 가뭄지수와 달리 증발/산 요구량 (evaporative demand)에 초점을 맞춰 보다 짧은 시간의 척도와 공간 분포 및 시계열 결과의 도출로 잠재적 가뭄 예보에 활용할 수 있어 가뭄의 조기 경보 및 가뭄 모니터링 도구로 사용할 수 있다. 현재 NOAA에서는 EDDI Map Archive(https://www.esrl.noaa.gov/psd/eddi/)를 활용하여 1980년부터 현재까지 1-week부터 12-months 시간척도의 미국 전역의 EDDI 지도를 제공하고 있으며, 짧은 기간의 급속하게 발생하는(rapid-onset) Flash drought의 조기경보지표로 활용되고 있다. 본 연구에서는 최근 3년간 우리나라에 발생한 극심한 가뭄 사상을 대상으로 EDDI의 적용함으로서 시공간적 가뭄 특성을 파악하고자 한다.

• Nuclear Engineering and Technology
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• 제53권10호
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• pp.3449-3459
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• 2021

With the increasing availability of high-performance computing (HPC) platforms, uncertainty quantification (UQ) and sensitivity analyses (SA) can be efficiently leveraged to optimize design parameters of complex engineering problems using modeling and simulation tools. The workflow involved in such studies heavily relies on HPC resources and hence requires pre-processing and post-processing capabilities of large amounts of data along with remote submission capabilities. The NEAMS Workbench addresses all aspects of the workflows involved in these studies by relying on a user-friendly graphical user interface and a python application program interface. This paper highlights the NEAMS Workbench capabilities by presenting a semiautomated coupling scheme between Dakota and any given package integrated with the NEAMS Workbench, yielding a simplified workflow for users. This new capability is demonstrated by running a SA of a turbulent flow in a pipe using the open-source Nek5000 CFD code. A total of 54 jobs were run on a HPC platform using the remote capabilities of the NEAMS Workbench. The results demonstrate that the semiautomated coupling scheme involving Dakota can be efficiently used for UQ and SA while keeping scripting tasks to a minimum for users. All input and output files used in this work are available in https://code.ornl.gov/neams-workbench/dakota-nek5000-study.

• International Journal of Computer Science & Network Security
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• 제21권8호
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• pp.369-376
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• 2021

One of the most active areas of research in the field of affective computing and signal processing is emotion recognition. This paper proposes emotion recognition of low-resource (Sindhi) language. This work's uniqueness is that it examines the emotions of languages for which there is currently no publicly accessible dataset. The proposed effort has provided a dataset named MAVDESS (Mehran Audio-Visual Dataset Mehran Audio-Visual Database of Emotional Speech in Sindhi) for the academic community of a significant Sindhi language that is mainly spoken in Pakistan; however, no generic data for such languages is accessible in machine learning except few. Furthermore, the analysis of various emotions of Sindhi language in MAVDESS has been carried out to annotate the emotions using line features such as pitch, volume, and base, as well as toolkits such as OpenSmile, Scikit-Learn, and some important classification schemes such as LR, SVC, DT, and KNN, which will be further classified and computed to the machine via Python language for training a machine. Meanwhile, the dataset can be accessed in future via https://doi.org/10.5281/zenodo.5213073.

• 셀메드
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• 제8권4호
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• pp.21.1-21.2
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• 2018

The aim of this article is to argue that repeated singing helps to feel 'misery loves company.' Folksong is popular music in the past. Korean folk songs have almost repetitive chorus. The repetitive refrain is made easy for everyone to follow. So, people become comrades who share the chorus together. Repetitive music makes people more intimate and more intimate. So, people feel that they share thoughts and feelings with music. It gives me energy to never give in to destiny. So, they encourage each other to be worth living. They sing together and sympathize and comfort each other's pain. 'Hook song' is the most popular form in these days in Korean music. The form of K-pop (Korean pop), which is gaining popularity worldwide, has many repetitions and concentration of melody. BTS (Bang Tan Sonyundan, Boyband) also tells teens around the world through repetitive melodies that "Let's share our joy and sorrow." This is the highest value of music therapy. BTS is a Korean boy band that has gained a worldwide reputation. Recently, their songs are affecting teenagers all over the world. In this way, the author thinks that the repetition of folk songs was reborn as a 'Hook song' and the repetitive form of music is a good way to give support to anyone. The author thinks this is best accomplished by singing 'misery loves company.'

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권2호
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• pp.1043-1063
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• 2019

With delegating proxy to process data before outsourcing, data owners in restricted access could enjoy flexible and powerful cloud storage service for productivity, but still confront with data integrity breach. Identity-based data auditing as a critical technology, could address this security concern efficiently and eliminate complicated owners' public key certificates management issue. Recently, Yu et al. proposed an Identity-Based Public Auditing for Dynamic Outsourced Data with Proxy Processing (https://doi.org/10.3837/tiis.2017.10.019). It aims to offer identity-based, privacy-preserving and batch auditing for multiple owners' data on different clouds, while allowing proxy processing. In this article, we first demonstrate this scheme is insecure in the sense that malicious cloud could pass integrity auditing without original data. Additionally, clouds and owners are able to recover proxy's private key and thus impersonate it to forge tags for any data. Secondly, we propose an improved scheme with provable security in the random oracle model, to achieve desirable secure identity based privacy-preserving batch public auditing with proxy processing. Thirdly, based on theoretical analysis and performance simulation, our scheme shows better efficiency over existing identity-based auditing scheme with proxy processing on single owner and single cloud effort, which will benefit secure big data storage if extrapolating in real application.

• Journal of Information Science Theory and Practice
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• 제10권4호
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• pp.3-22
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• 2022

This paper provides an overview of the emergence of resource discovery systems and services, along with their advantages, best practices, and current landscapes. It outlines some of the key services and functionalities of a comprehensive discovery model suitable for academic libraries in developing countries. The proposed model (VuFind as a discovery tool) performs like other existing web-scale resource discovery systems, both commercial and open-source, and is capable of providing information resources from different sources in a single-window search interface. The objective of the paper is to provide seamless access to globally distributed subscribed as well as open access resources through its discovery interface, based on a unified index. This model uses Koha, DSpace, and Greenstone as back-ends and VuFind as a discovery layer in the front-end and has also integrated many enhanced search features like Bento-box search, Geodetic search, and full-text search (using Apache Tika). The goal of this paper is to provide the academic community with a one-stop shop for better utilising and integrating heterogeneous bibliographic data sources with VuFind (https://vufind.org/vufind).

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권5호
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• pp.1778-1797
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• 2021

Document image binarization is an important pre-processing step in document analysis and archiving. The state-of-the-art models for document image binarization are variants of encoder-decoder architectures, such as FCN (fully convolutional network) and U-Net. Despite their success, they still suffer from three limitations: (1) reduced feature map resolution due to consecutive strided pooling or convolutions, (2) multiple scales of target objects, and (3) reduced localization accuracy due to the built-in invariance of deep convolutional neural networks (DCNNs). To overcome these three challenges, we propose an improved semantic segmentation model, referred to as DP-LinkNet, which adopts the D-LinkNet architecture as its backbone, with the proposed hybrid dilated convolution (HDC) and spatial pyramid pooling (SPP) modules between the encoder and the decoder. Extensive experiments are conducted on recent document image binarization competition (DIBCO) and handwritten document image binarization competition (H-DIBCO) benchmark datasets. Results show that our proposed DP-LinkNet outperforms other state-of-the-art techniques by a large margin. Our implementation and the pre-trained models are available at https://github.com/beargolden/DP-LinkNet.

• 아태비즈니스연구
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• 제13권3호
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• pp.375-387
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• 2022

Purpose - The food delivery mobile application market is growing rapidly in the catering service industry. The purpose of this study was to investigate the effects of E-service quality on consumer attitudes and satisfaction in the food delivery service field in China. Design/methodology/approach - A total of 390 copies of this questionnaire were distributed between February 17 and March 25, 2021 on the Chinese survey site (https://www.wjx.cn). Three hundred forty-nine parts were used for the final analysis. Validity and reliability were analyzed using SPSS 25.0 statistical program, and correlation and regression analysis were performed. Findings - The study results showed among the e-service quality components of food delivery application software, trust, convenience, proximity and reactivity have an impact on consumer attitudes. Research implications or Originality - The service quality of food application software is an important factor determining consumer attitude. The limitations of this study and suggestions for future research were discussed.

• The Journal of Asian Finance, Economics and Business
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• 제8권9호
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• pp.249-260
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• 2021

This research explores the effects of intellectual capital on knowledge management processes (creation of information, knowledge sharing, and use of knowledge) and innovation performance. The data was gathered from 224 fashion accessories in Thailand using a questionnaire. The population was collected on December 16, 2019 (https:/www.ditp.go.th) from a list database of the Department of International Trade Promotion, Ministry of Commerce of Thailand (2019). A questionnaire mail survey technique was used to collect data. Executives or managers were the key participants in this study. The statistical technique used to analyze is the ordinary least square regression. The findings show that intellectual capital has a significant positive effect on information management systems. Likewise, information management techniques have a significant positive effect on innovation performance. Moreover, increasing the use of information tends to make staff willing to use the knowledge to improve the quality and quantity of the service. This tendency contributes to productivity gain. Through the interaction of processes of information use, self-reflection, and input from customers, employees tend to increase the production of knowledge that eventually develops the results of the innovation. Hence, organizations should value knowledge management process elements to improve efficiency, and thus innovation.