• 한국물환경학회지
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• 제27권5호
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• pp.670-679
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• 2011

Chlorophyll-a is a major water quality indicator for an algal bloom in streams and lakes. The purpose of the study is to estimate chlorophyll-a concentration in tributaries of the Seonakdonggang by an artificial neural network (ANN). As the tributaries are ungauged streams, a watershed runoff and quality model was used to simulate water quality parameters. The tributary watersheds include urban area and thus Storm Water Management Model (SWMM) was used to simulate TN, TP, BOD, COD, and SS. SWMM, however, can not simulate chlorophyll-a. The chlorophyll-a series data from the tributaries were estimated by the ANN and the simulation results of water quality parameters using SWMM. An assumption used is as follows: the relation between water quality parameters and chlorophyll-a in the tributaries of the Seonakdonggang would be similar to that in the mainstream of the Seonakdonggang. On the assumption, the measurement data of water quality and chlorophyll-a in the mainstream of the Seonakdonggang were used as the learning data of the ANN. Through the sensitivity analysis, the learning data combination of water quality parameters was determined. Finally, chlorophyll-a series were estimated for tributaries of the Seonakdonggang by the ANN and TN, TP, BOD, COD, and temperature data from those streams. The relative errors between the estimated and measured chlorophyll-a were approximately 40 ~ 50%. Though the errors are somewhat large, the estimation process for chlorophyll-a may be useful in ungauged streams.

• International Journal of Computer Science & Network Security
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• 제22권4호
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• pp.111-118
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• 2022

This research article presents the work that is related to the application of different machine learning based similarity techniques on religious text for identifying similarities and differences among its various translations. The dataset includes 10 different English translations of verses (Arabic: Ayah) of two Surahs (chapters) namely, Al-Humazah and An-Nasr. The quantitative similarity values for different translations for the same verse were calculated by using the cosine similarity and semantic similarity. The corpus went through two series of experiments: before pre-processing and after pre-processing. In order to determine the performance of machine learning based similarities, human annotated similarities between translations of two Surahs (chapters) namely Al-Humazah and An-Nasr were recorded to construct the ground truth. The average difference between the human annotated similarity and the cosine similarity for Surah (chapter) Al-Humazah was found to be 1.38 per verse (ayah) per pair of translation. After pre-processing, the average difference increased to 2.24. Moreover, the average difference between human annotated similarity and semantic similarity for Surah (chapter) Al-Humazah was found to be 0.09 per verse (Ayah) per pair of translation. After pre-processing, it increased to 0.78. For the Surah (chapter) An-Nasr, before preprocessing, the average difference between human annotated similarity and cosine similarity was found to be 1.93 per verse (Ayah), per pair of translation. And. After pre-processing, the average difference further increased to 2.47. The average difference between the human annotated similarity and the semantic similarity for Surah An-Nasr before preprocessing was found to be 0.93 and after pre-processing, it was reduced to 0.87 per verse (ayah) per pair of translation. The results showed that as expected, the semantic similarity was proven to be better measurement indicator for calculation of the word meaning.

• 한국미생물·생명공학회지
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• 제49권2호
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• pp.157-166
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• 2021

The probiotic market is constantly continuing to grow, concomitantly with a widening in the range and diversity of probiotic products. Probiotics are defined as live microorganisms that provide a benefit to the host when consumed at a proper dose; the viability of a probiotic is therefore of crucial importance for its efficacy. Many products undergo lyophilization for maintaining their shelf-life. Unfortunately, this procedure may damage the integrity of the cells due to stress conditions during both the freezing and (vacuum-) drying process, thereby impacting their functionality. We propose a lysine-based mixture for rehydration of freeze-dried probiotics for improving their viability during in vitro simulated gastric and duodenum stress conditions. Measurement of the zeta potential served as an indicator of cell integrity and efficacy of this mixture, while functionality was estimated by adhesion to a human enterocyte-like Caco-2 cell-line. The freeze-dried bacteria exhibited a significantly different zeta potential compared to fresh cultures; however, this condition could be restored by rehydration with the lysine mixture. Recovery of the surface charge was found to influence adhesion ability to the Caco-2 cell-line. The optimum lysine concentration of the formulation, designated "Zeta-bio", was found to be 0.03 M for improving the viability of Lactiplantibacillus plantarum Lp-115 by up to 13.86% and a 7-strain mixture (400B) to 41.99% compared to the control rehydrated with distilled water. In addition, the lysine Zeta-bio formulation notably increased the adherence ability of lyophilized Lp-115 to the Caco-2 cell-line after subjected to the in vitro stress conditions of the simulated gastrointestinal tract passage.

• 한국건축시공학회지
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• 제22권2호
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• pp.207-218
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• 2022

생산 과정이 이루어지는 공간적 범위 내에서 발생하는 거시환경 변화는 대표적인 수주산업의 하나인 건설산업의 단위 프로젝트 성과에 직접적인 영향을 미칠 수 있는 요인이 될 수 있다. 이와 같은 거시환경 변화는 성공적인 사업 성과 달성을 위한 전제조건임에도 불구하고, 선행 연구는 생산과정 내에서의 성과관리를 위한 방안들을 주요 결과로 제시하고 있다. 이에 본 연구는 국내 건설 프로젝트를 대상으로 거시적 측면에서의 환경 변화를 분석하여 성과에 영향을 미칠 수 있는 지표 도출을 제안하였다. 주요 영향지표는 관련 법령 및 정책, 미래전략보고서 등의 주요 분석 내용을 기초로 도출된 중점 키워드를 조합하여 설정하였으며, 지표별 중요도는 계층적 의사결정기법을 통해 정량적으로 검토하였다. 본 연구의 결과는 건설 프로젝트의 다양한 이해관계자들이 성공적인 성과 달성을 위한 전략 수립 시 참고할 수 있는 유의미한 기초자료로서 활용이 가능할 것으로 예상된다.

• 한국산업정보학회논문지
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• 제27권6호
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• pp.1-12
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• 2022

음원 스트리밍 서비스와 Hi-Fi 시장이 성장함에 따라 다양한 음향기기들이 출시되고 있다. 이로 인해 소비자들의 제품 선택에 대한 폭은 넓어졌지만 자신의 음악적 취향과 일치하는 제품을 찾기는 더욱 어려워졌다. 본 연구에서는 사용자가 선호하는 음원으로부터 보컬 성분을 추출하고 이를 토대로 사용자에게 가장 적합한 음향기기를 추천하는 시스템을 제안하였다. 이를 위해 먼저 원본 음원을 Python의 Spleeter Library를 통해 분리하여 보컬 음원을 추출하고 제조사의 음향기기의 주파수 대역 데이터를 수집한 결과를 각각 격자 그래프로 나타내었다. 추출한 보컬 음원의 주파수 대역과 음향기기의 주파수 대역 측정치 데이터를 비교하기 위한 지표로서 Matching Gap Index(MGI)를 제안하였다. 산출된 MGI 값을 토대로 사용자 선호와의 유사도가 가장 높은 음향기기를 추천한다. 추천 결과는 음향 전문업체에서 제공하는 장르별 Equalizer 데이터를 이용하여 검증하였다.

• 국제학술발표논문집
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• The 3th International Conference on Construction Engineering and Project Management
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• pp.1599-1607
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• 2009

In order to deal with severe competition in the construction market of developing countries, large contractors must continually improve their own performance and operation. Performance measurement is the heart of ceaseless improvement in organizations. Key performance indicators (KPIs) play a key role in measuring project management performance (PMP) of large contractors in developing countries. The main objective of this paper is to identify KPIs, which can be used to measure PMP of contractors, and then analyze the underlying relationships of these KPIs in order to gain insight into PMP of large construction firms in Vietnam construction industry (VCI). Literature reviews and the pilot survey provided 30 KPIs. Fourteen KPIs, which have the mean values higher than 3.0, were considered as important KPIs through a questionnaire survey of 32 professionals. Factor analysis of these KPIs was employed to categorize them. The results of the survey revealed that top six KPIs are construction time and cost, owner satisfaction on services and products, and quality management and project team performance. Factor analysis uncovered that 14 top-ranked KPIs can be grouped under six categories, namely: (1) construction input management, (2) owner satisfaction, (3) cost and quality, (4) manpower management, (5) subcontractor performance and (6) equipment management. The findings of this research can be used as a guideline to measure PMP of contractors in Vietnam as well as in other developing countries. Since contractors from a country to the other country may have the same manner to manage construction projects, the results of this study may be useful not only to practitioners and researchers in Vietnam but also to participants in other developing countries.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2011년도 춘계학술발표대회
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• pp.346-349
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• 2011

In this paper, we design a perceptually invisible dot pattern layout and its recognition scheme, and we apply the recognition scheme into a smart self learning aid for interactive learning aid. To increase maximum information capacity and also increase robustness to the noises, we design a ECC (error correcting code) based dot pattern with directional vector indicator. To make a smart self-learning aid, we embed the micro dot pattern (20 information bit + 15 ECC bits + 9 layout information bit) using K ink (CMYK) and extract the dot pattern using IR (infrared) LED and IR filter based camera, which is embedded in the smart pen. The reason we use K ink is that K ink is a carbon based ink in nature, and carbon is easily recognized with IR even without light. After acquiring IR camera images for the dot patterns, we perform layout adjustment using the 9 layout information bit, and extract 20 information bits from 35 data bits which is composed of 20 information bits and 15 ECC bits. To embed and extract information bits, we use topology based dot pattern recognition scheme which is robust to geometric distortion which is very usual in camera based recognition scheme. Topology based pattern recognition traces next information bit symbols using topological distance measurement from the pivot information bit. We implemented and experimented with sample patterns, and it shows that we can achieve almost 99% recognition for our embedding patterns.

• Journal of Korea Trade
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• 제26권7호
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• pp.127-144
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• 2022

Purpose - This study aimed to analyze the dynamic effects of progress in globalization on firm performance by employing individual companies' financial statement datasets. Design/methodology - The analysis leveraged the variables of operating revenue (OPRE) and pre-tax profit and loss (PLBT) as measurement variables for firm performance over 2011-2019. As a proxy variable for globalization, the trade index, a subordinate indicator of the KOF Globalization Index, was used. Through panel regression analysis, the relationship among those variables was ascertained, and the local projection (LP) method was subsequently utilized to identify dynamic effects. A subsample analysis was further performed by classifying companies based on their sizes and industries to determine the differential effects of globalization on each group. Findings - The panel regression analysis derived positive effects of an increasing degree of globalization on OPRE of Korea maritime and fishery firms. However, the impulse response functions, obtained from the LP, showed that in the short run, globalization affects PLBT negatively but in the long run, it gradually converted into a positive effect. In addition, according to the subsample analysis based on company size, the effects of globalization on OPRE became greater as each company became larger. Moreover, the industry-based analysis showed heterogeneous effects, depending on the industries in which the maritime and fishery companies operated. Originality/value - The analysis of the dynamic effects of globalization on firm performance, which revealed that the effects vary depending on the time points, is the important contribution of this study. The results also suggest that the effects of globalization vary depending on the company size and industry.

• 전기전자학회논문지
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• 제26권1호
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• pp.62-66
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• 2022

최근 데이터 기반의 딥러닝 기술을 적용하여 비면허 대역의 다양한 통신 신호를 분류하는 연구가 활발히 수행되고 있다. 하지만, 복잡한 신경망 모델 사용을 기반으로 이뤄진 이러한 접근법은 높은 연산 능력을 필요로 하게 되어, 자원 제약적인 무선 인터페이스 및 사물인터넷(Internet of Things) 장비에서는 사용이 제약된다. 본 연구에서는 비면허 대역의 무선 이기종 기술을 인지하기 위한 데이터 기반의 접근 방법을 살펴보고, 신호의 특징 추출 및 데이터화의 효율화 문제를 다룬다. 구체적으로, 비면허 대역의 다른 종류의 무선 통신 기술을 구분하기 위해 수신 신호 강도 측정을 기반으로 한 시계열 데이터를 이용해 합성곱 신경망(Convolutional Neural Network, CNN) 모델을 학습시켜 신호를 분류하는 방법을 살펴본다. 이 과정에서 동일한 구조의 신경망 모델의 경량화를 위한 효율적 신호의 시계열 데이터 정보 수집시 주파수 대역의 특징을 함께 특징화하는 방법을 제안하고, 그 효과를 평가한다. Bluetooth 호환의 Ubertooth 장비를 이용한 실측 기반의 실험 결과는 제안된 샘플링 기법이 동일한 신경망에 대해서 10% 수준의 샘플링 데이터 이용만으로도 동일한 정확도를 유지함을 보여준다.

• 천문학회보
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• 제46권2호
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• pp.40.3-41
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• 2021

Minor mergers leave behind long lived, but extremely faint and extended tidal features including tails, streams, loops and plumes. These act as a fossil record for the host galaxy's past interactions, allowing us to infer recent accretion histories and place constraints on the properties and nature of a galaxy's dark matter halo. However, shallow imaging or small homogeneous samples of past surveys have resulted in weak observational constraints on the role of galaxy mergers and interactions in galaxy assembly. The Rubin Observatory, which is optimised to deliver fast, wide field-of-view imaging, will enable deep and unbiased observations over the 18,000 square degrees of the Legacy Survey of Space and Time (LSST), resulting in samples of potentially of millions of objects undergoing tidal interactions. Using realistic mock images produced with state-of-the-art cosmological simulations we perform a comprehensive theoretical investigation of the extended diffuse light around galaxies and galaxy groups down to low stellar mass densities. We consider the nature, frequency and visibility of tidal features and debris across a range of environments and stellar masses as well as their reliability as an indicator of galaxy accretion histories. We consider how observational biases such as projection effects, the point-spread-function and survey depth may effect the proper characterisation and measurement of tidal features, finding that LSST will be capable of recovering much of the flux found in the outskirts of L* galaxies at redshifts beyond local volume. In our simulated sample, tidal features are ubiquitous In L* galaxies and remain common even at significantly lower masses (M*>10^10 Msun). The fraction of stellar mass found in tidal features increases towards higher masses, rising to 5-10% for the most massive objects in our sample (M*~10^11.5 Msun). Such objects frequently exhibit many distinct tidal features often with complex morphologies, becoming increasingly numerous with increased depth. The interpretation and characterisation of such features can vary significantly with orientation and imaging depth. Our findings demonstrate the importance of accounting for the biases that arise from projection effects and surface-brightness limits and suggest that, even after the LSST is complete, much of the discovery space in low surface-brightness Universe will remain to be explored.