• Title/Summary/Keyword: a real-time analysis

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Cloning and sequence analysis of Wild Argali short palate, lung and nasal epithelium clone 1 cDNA

  • Shen, Wen;Chen, Kaili;Sun, Yanming;Guo, Haiying;Chen, Dongmei;Cao, Yang
    • Asian-Australasian Journal of Animal Sciences
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    • v.30 no.5
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    • pp.736-742
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    • 2017
  • Objective: Experiments were conducted to clone the sequence of Wild Argali short palate, lung and nasal epithelium clone 1 (SPLUNC1) cDNA, and to lay the foundation for further study the biological function of Wild Argali SPLUNC1. Methods: The complete sequence of Wild Argali SPLUNC1 cDNA was generated by rapid amplification of cDNA ends. The entire coding sequence was inserted into the pPIC9K vector and expressed in Pichia pastoris (P. pastoris) GS115. The recombinant SPLUNC1 protein was detected by Western blot and purified by $Ni^{2+}$ chelate affinity chromatography. The test of effect of the protein on Mycoplasma ovipneumoniae (MO) was performed with real-time polymerase chain reaction. Results: The Wild Argali SPLUNC1 cDNA was 1,076 bp with an open reading frame of 768 bp, which encoded a 26.49 kDa protein composed of 255 amino acids. Its amino acid sequence shared 98.4%, 96.9%, 94.5%, 90.2%, 80.8%, 78.4%, 78.3%, 72.5%, 72.3%, 68.8% identity with those of SPLUNC1 cDNA from Ovis aries (accession no. NP_001288334.1), Capra hircus (accession no. XP_005688516.1), Pantholops hodgsonii (accession no. XP_005979709.1), Bos taurus (accession no. NP_776851.1), Felis catus (accession no. XP_006929910.1), Homo sapiens (accession no. NP_001230122.1), Sus scrofa (accession no. NP_001005727.1), Chinchilla lanigera (accession no. NP_001269294.1), Mus musculus (accession no. NP_035256.2), and Rattus norvegicus (accession no. NP_742028.1), respectively. The recombinant protein corresponded to the expected molecular mass of 25.47 kDa as judged by sodium dodecyl sulfate-polyacrylamide gel electrophoresis, and it was detected in the supernatant of P. pastoris, and it could be purified. The results from the test of inhibition effect of argali recombinant SPLUNC1 protein on MO showed that the product could inhibit MO very well (p<0.01). Conclusion: The amino acid sequence of Wild Argali SPLUNC1 was different from other organisms. The recombinant SPLUNC1 protein has good biological activity.

GIS Based Real-Time Transit Information Integration and Its Transit Planning Implications

  • Hwang, Da-Hae;Kim, Dong-Young;Choi, Yun-Soo;Cho, Seong-Kil
    • Journal of Korean Society for Geospatial Information Science
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    • v.15 no.2 s.40
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    • pp.87-93
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    • 2007
  • Over the years, Advanced Public Transportation System (APTS) has been implemented to manage and operate public transportation system. With the expanding mass spatio-temporal data such as comprehensive spatial information of each individual passenger and public transportation vehicle, it has been required to consolidate and analyze these multiple data sets from various sources. This paper demonstrates how GIS is utilized for the consolidation of massive transit related spatio-temporal information. And it presents effective applications to improve transit planning process and support transit related decision-making activities. GIS based system is used to combine multi-agents' data in the areas of transit operation and individual transit ride and transfer management. Due to the unique comprehensiveness and the level of detail of the data provide by the Seoul Transit system, this GIS based information consolidation is the first in its class. Based on the integrated database, this paper describes the effective and efficient GIS based analysis deployed in a transportation system planning process. The data integration systems and analytic models developed in this paper can be transferred and applied by any municipal governments provided that the appropriate data is available.

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Measurement of the Size Distribution of Smoke Particles with Plastic Types Under Various Fire Conditions (다양한 화재조건에서 플라스틱 종류에 따른 연기입자의 크기분포 변화 측정)

  • Goo, Jaehark;Hwang, Cheol-Hong
    • Fire Science and Engineering
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    • v.31 no.6
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    • pp.8-15
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    • 2017
  • Most fire victims succumb to smoke inhalation, and fire smoke toxicity from interior materials is increasing with increased use of plastics. Large amounts of hazardous effects of smoke are related to deposition of smoke particles in respiratory tracts, and deposition characteristics are influenced by size distribution of particles. Thus, it is essential to know the size distribution of smoke particles from plastics for hazard analysis of fire smoke. In a recent study, it has been shown that size distributions of smoke particles from PP are different from wood in many aspects. In order to know whether other plastics show the same characteristics as PP, size distributions of smoke particles from four plastic materials (LDPE, PA66, PMMA, and PVC) were measured in real time under each fire type with various temperature and oxygen supply. In this study, smoke particles from different plastics were generated uniformly by using steady-state tube furnace method provided in ISO/TS 19700. Their size distributions were measured by using an electrical low pressure impactor (ELPI). Results of measurements showed that size distributions of smoke particles from these four plastic materials were similar to those from PP in many aspects. However, they were distinctively different from those of wood.

Development of the RP and SP Combined using Error Component Method (Error Component 방법을 이용한 RP.SP 결합모형 개발)

  • 김강수;조혜진
    • Journal of Korean Society of Transportation
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    • v.21 no.2
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    • pp.119-130
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    • 2003
  • SP data have been widely used in assessing new transport policies and transport related plans. However, one of criticisms of using SP is that respondents may show different reaction between hypothetical experiments and real life. In order to overcome the problem, combination of SP and RP data has been suggested and the combined methods have been being developed. The purpose of this paper is to suggest a new SP and RP combined method using error component method and to verify the method. The error component method decomposes IID extreme value error into non-IID error component(s) and an IID error component. The method estimates both of component parameters and utility parameters in order to obtain relative variance of SP data and RP data. The artificial SP and RP data was created by using simulation and used for the analysis, and the estimation results of the error component method were compared with those of existing SP and RP combined methods. The results show that regardless of data size, the parameters of the error component method models are similar to those assumed parameters much more than those of the existing SP and RP combined models, indicating usefulness of the error component method. Also the values of time for error component method are more similar to those assumed values than those of the existing combined models. Therefore, we can conclude that the error component method is useful in combining SP and RP data and more efficient than the existing methods.

A Study on Estimation for Freight Transportation Indices on Expressway Using TCS and WIM Data (TCS 및 WIM 자료를 활용한 고속도로 물동량 지표 산정방안에 관한 연구)

  • OH, Junghwa;KIM, Hyunseung;PARK, Minseok;CHOI, Yoonhyuk;KWON, Soonmin;PARK, Dongjoo
    • Journal of Korean Society of Transportation
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    • v.35 no.5
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    • pp.458-467
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    • 2017
  • The expressway of the Korea has an important role in freight movement because 76 percent of the commodity is transported by trucks. However, there has been few indices on the role of expressways regarding freight transportation and truck traffic. The objective of this study is to propose four freight transportation related indices using ITS-related system such as TCS and HS-Wim: total truck's travel miles ($veh{\cdot}km/year$), total freight transport miles ($ton{\cdot}km/year$). efficiency of truck's travel ($veh{\cdot}km/km$), and efficiency of freight movement ($ton{\cdot}km/km$). These truck and freight related indices were estimated and compared by two different data sources: traffic volume data using VDS and OD data using TCS. These indices were designed to estimated on real time and updated every day and month.

Effective brain-wave DB building system using the five senses stimulation (오감자극을 활용한 효율적인 뇌파 DB구축 시스템)

  • Shin, Jeong-Hoon;Jin, Sang-Hyeon
    • Journal of the Institute of Convergence Signal Processing
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    • v.8 no.4
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    • pp.227-236
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    • 2007
  • Ubiquitous systems have grown explosively over the few years. Nowadays users' needs for high qualify service lead a various type of user terminals. One of various type of user interface, various types of effective human computer interface methods have been developed. In many researches, researchers have focused on using brain-wave interface, that is to say, BCI. Nowadays, researches which are related to BCI are under way to find out effective methods. But, most researches which are related to BCI are not centralized and not systematic. These problems brought about ineffective results of researches. In most researches related in HCI, that is to say - pattern recognition, the most important foundation of the research is to build correct and sufficient DB. But there is no effective and reliable standard research conditions when researchers are gathering brain-wave in BCI. Subjects as well as researchers do not know effective methods for gathering DB. Researchers do not know how to instruct subjects and subjects also do not know how to follow researchers' instruction. To solve these kinds of problems, we propose effective brain-wave DB building system using the five senses stimulation. Researcher instructs the subject to use the five senses. Subjects imagine the instructed senses. It is also possible for researchers to distinguish whether brain-wave is right or not. In real time, researches verify gathered brain-wane data using spectrogram. To verify effectiveness of our proposed system, we analyze the spectrogram of gathered brain-wave DB and pattern. On the basis of spectrogram and pattern analysis, we propose an effective brain-wave DB building method using the five senses stimulation.

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Deduction of Data Quality Control Strategy for High Density Rain Gauge Network in Seoul Area (서울시 고밀도 지상강우자료 품질관리방안 도출)

  • Yoon, Seongsim;Lee, Byongju;Choi, Youngjean
    • Journal of Korea Water Resources Association
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    • v.48 no.4
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    • pp.245-255
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    • 2015
  • This study used high density network of integrated meteorological sensor, which are operated by SK Planet, with KMA weather stations to estimate the quantitative precipitation field in Seoul area. We introduced SK Planet network and analyzed quality of the observed data for 3 months data from 1 July to 30 September 2013. As the quality analysis result, we checked most SK Planet stations observed similar with previous KMA stations. We developed the real-time quality check and adjustment method to reduce the error effect for hydrological application by missing and outlier value and we confirmed the developed method can be corrected the missing and outlier value. Through this method, we used the 190 stations(KMA 34 stations, SK Planet 156 stations) that missing ratio is less than 20% and the effect of the outlier was the smallest for quantitative precipitation estimation. Moreover, we evaluated reproducibility of rainfall field high density rain gauge network has $3km^2$/gauge. As the result, the spatial relative frequency of rainfall field using SK Planet and KMA stations is similar with radar rainfall field. And, it supplement the blank of KMA observation network. Especially, through this research we will take advantage of the density of the network to estimate rainfall field which can be considered as a very good approximation of the true value.

Social Factors Affecting Internet Searches on Cyber Bullying in Korea and America Using Social Big Data and Google Search Trends (소셜 빅데이터와 Google 검색트렌드를 활용한 한국과 미국의 사이버불링 검색에 영향을 미치는 요인 분석)

  • Song, Tae-Min;Song, Juyoung;Cheon, Mi-Kyung
    • The Journal of Bigdata
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    • v.1 no.1
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    • pp.67-75
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    • 2016
  • The study analyzed big data extracted from Google and social media to identify factors related to searches on cyber bullying in Korea and America. Korea's cyber bullying analysis was conducted social big data collected from online news sites, blogs, $caf{\acute{e}}s$, social network services and message for between January 1, 2011 and March 31, 2013. Google search trends for the search words of stress, exercise, drinking, and cyber bullying were obtained for January 1, 2004 and December 22, 2013. The main results of this study were as follows: first, the significant factors stress were cyber bullying that Korea more than America. Secondly, a positive relationship was found between stress and drinking, exercise and cyber bullying both Korea and America. Thirdly, significant differences were found all path both Korea and America. The study shows that both adults and teenagers are influenced in Korea. We need to develop online application that if cyber bullying behavior was predicted can intervene in real time because these actual cyber bullying-related exposure to psychological and behavioral characteristic.

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Short-Term Prediction of Vehicle Speed on Main City Roads using the k-Nearest Neighbor Algorithm (k-Nearest Neighbor 알고리즘을 이용한 도심 내 주요 도로 구간의 교통속도 단기 예측 방법)

  • Rasyidi, Mohammad Arif;Kim, Jeongmin;Ryu, Kwang Ryel
    • Journal of Intelligence and Information Systems
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    • v.20 no.1
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    • pp.121-131
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    • 2014
  • Traffic speed is an important measure in transportation. It can be employed for various purposes, including traffic congestion detection, travel time estimation, and road design. Consequently, accurate speed prediction is essential in the development of intelligent transportation systems. In this paper, we present an analysis and speed prediction of a certain road section in Busan, South Korea. In previous works, only historical data of the target link are used for prediction. Here, we extract features from real traffic data by considering the neighboring links. After obtaining the candidate features, linear regression, model tree, and k-nearest neighbor (k-NN) are employed for both feature selection and speed prediction. The experiment results show that k-NN outperforms model tree and linear regression for the given dataset. Compared to the other predictors, k-NN significantly reduces the error measures that we use, including mean absolute percentage error (MAPE) and root mean square error (RMSE).

Effects of 17β-Estradiol on Colonic Permeability and Inflammation in an Azoxymethane/Dextran Sulfate Sodium-Induced Colitis Mouse Model

  • Song, Chin-Hee;Kim, Nayoung;Sohn, Sung Hwa;Lee, Sun Min;Nam, Ryoung Hee;Na, Hee Young;Lee, Dong Ho;Surh, Young-Joon
    • Gut and Liver
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    • v.12 no.6
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    • pp.682-693
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    • 2018
  • Background/Aims: Intestinal barrier dysfunction is a hallmark of inflammatory bowel diseases (IBDs) such as ulcerative colitis. This dysfunction is caused by increased permeability and the loss of tight junctions in intestinal epithelial cells. The aim of this study was to investigate whether estradiol treatment reduces colonic permeability, tight junction disruption, and inflammation in an azoxymethane (AOM)/dextran sodium sulfate (DSS) colon cancer mouse model. Methods: The effects of $17{\beta}$-estradiol (E2) were evaluated in ICR male mice 4 weeks after AOM/DSS treatment. Histological damage was scored by hematoxylin and eosin staining and the levels of the colonic mucosal cytokine myeloperoxidase (MPO) were assessed by enzyme-linked immunosorbent assay (ELISA). To evaluate the effects of E2 on intestinal permeability, tight junctions, and inflammation, we performed quantitative real-time polymerase chain reaction and Western blot analysis. Furthermore, the expression levels of mucin 2 (MUC2) and mucin 4 (MUC4) were measured as target genes for intestinal permeability, whereas zonula occludens 1 (ZO-1), occludin (OCLN), and claudin 4 (CLDN4) served as target genes for the tight junctions. Results: The colitis-mediated induced damage score and MPO activity were reduced by E2 treatment (p<0.05). In addition, the mRNA expression levels of intestinal barrier-related molecules (i.e., MUC2, ZO-1, OCLN, and CLDN4) were decreased by AOM/DSS-treatment; furthermore, this inhibition was rescued by E2 supplementation. The mRNA and protein expression of inflammation-related genes (i.e., KLF4, NF-${\kappa}B$, iNOS, and COX-2) was increased by AOM/DSS-treatment and ameliorated by E2. Conclusions: E2 acts through the estrogen receptor ${\beta}$ signaling pathway to elicit anti-inflammatory effects on intestinal barrier by inducing the expression of MUC2 and tight junction molecules and inhibiting pro-inflammatory cytokines.