• Title/Summary/Keyword: Detection probability

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Triple Detector SPECT Imaging with $^{99m}Tc-DMSA$ in Adult Patients with Urinary Tract Infection (성인 요로 감염 환자에서 $^{99m}Tc-DMSA$ 삼중검출기 SPECT 영상의 유용성)

  • Ryu Jin-Sook;Bae, Won-Gyu;Moon Dae-Hyuk;Lee, Myung-Hae;Kim, Soon-Bae,;Park, Su-Kil;Park, Jung-Sik;Hong, Chang-Gi D.;Cho, Kyung-Sik
    • The Korean Journal of Nuclear Medicine
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    • v.26 no.2
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    • pp.290-298
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    • 1992
  • Although early diagnosis of urinary tract infection is important, the radiologic evaluation is still controversial because of the low sensitivity and the lack of cost-effectiveness. This study was carried out to evaluate the clinical utility of high resolution triple head $^{99m}Tc-DMSA$ SPECT imaging in urinary tract infection. We prospectively performed $^{99m}Tc-DMSA$ planar and SPECT imaging, ultrasound of kidney (US), intravenous pyelography (IVP) and voiding cystourethrography (VCU) in all 60 adult patients with UTI [26 with first episode of acute pyelonephritis (APN), 22 with recurrent APN, and 12 persistent asymptomatic pyuria] and 25 normal persons. To assess reversibility of the renal cortical defect (RCD), $^{99m}Tc-DMSA$ SPECT was repeated 1 to 8 months later in those patients with abnormal initial findings. Overall detection rate of $^{99m}Tc-DMSA$ SPECT imaging was 83% (50/60), but planar, US, IVP and VCU showed abnormal findings in 68%, 28%, 32% and 13%, respectively. 25 out of 27 patients with normal or single RCD were all normal in other radioligic studies. Only two patients showed vesicoureteral reflux (VUR) on VCU (grade I) and mild hydronephrosis on IVP. But, high proportion of those with multiple RCD showed abnormal findings on US (17/33), IVP (18/33), and VCU (7/33): 67% in any of these 3 studies. Especially, 3 out 7 patients with VUR showed multiple RCD on $^{99m}Tc-DMSA$ SPECT without any abnormality on IVP or US. 25 normal persons showed normal findings in all studies except one false positive finding on $^{99m}Tc-DMSA$ SPECT imaging. Follow-up $^{99m}Tc-DMSA$ SPECT was done in 28 patients (13 with single RCD, 15 with multiple RCD). All 13 patients with single RCD showed improvement. Those with multiple RCD presented improvement in 4, no change in 10, and aggravation in 1 on follow-up studies. With these results, we conclude: 1) $^{99m}Tc-DMSA$ SPECT imaging is superior to planar imaging, US, IVP or VCU in detection of renal lesion in urinary tract infection. $^{99m}Tc-DMSA$ SPECT is useful as a initial diagnostic tool in adult patients with urinary tract infection. 2) The multiple RCD on $^{99m}Tc-DMSA$ SPECT represent the high probability of irreversible tissue change and need of extensive urological work-up.

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Monitoring of Residual Pesticides in Pepper Seed Oil Products Sold on the Market (고추씨 기름의 잔류농약 모니터링)

  • Mi-Hui Son;Jae-Kwan Kim;You-Jin Lee;Ji-Eun Kim;Eun-Jin Baek;Byeong-Tae Kim;Myoung-Ki Park;Yong-Bae Park
    • Journal of Food Hygiene and Safety
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    • v.38 no.6
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    • pp.483-488
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    • 2023
  • The status of residual pesticides was investigated in four pepper seed oil samples and 36 pepper-flavored oil samples oil distributed on the market from August to December 2022. A total of 179 pesticides were monitored in 40 samples, and 14 pesticides were detected in 39 of the samples, with a detection range of 0.01-2.16 mg/kg. In chili seed oil, 10 pesticides were detected 27 times with a range of 0.11-2.16 mg/kg, and in pepper-flavored oil, 9 pesticides were detected 94 times with a range of 0.01-0.80 mg/kg. The most frequently detected pesticides were tebuconazole, ethion, and difenoconazole, with ethion being detected in large concentrations in products using Chinese raw materials. Ethion, an unregistered pesticide in the Republic of Korea, has not been detected in the Gyeonggi-do area in the past 10 years. It is thought that the detection of ethion can be utilized as an indicator of products made in China. Peppers are a representative agricultural product for which many pesticides are used, and if the pesticides transferred to pepper seeds are not removed, the probability of detecting various types of pesticides in pepper seed oil is very high. Therefore, continuous research is needed to ensure the safety of pepper seed oil.

APPLICATION OF FUZZY SET THEORY IN SAFEGUARDS

  • Fattah, A.;Nishiwaki, Y.
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1993.06a
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    • pp.1051-1054
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    • 1993
  • The International Atomic Energy Agency's Statute in Article III.A.5 allows it“to establish and administer safeguards designed to ensure that special fissionable and other materials, services, equipment, facilities and information made available by the Agency or at its request or under its supervision or control are not used in such a way as to further any military purpose; and to apply safeguards, at the request of the parties, to any bilateral or multilateral arrangement, or at the request of a State, to any of that State's activities in the field of atomic energy”. Safeguards are essentially a technical means of verifying the fulfilment of political obligations undertaken by States and given a legal force in international agreements relating to the peaceful uses of nuclear energy. The main political objectives are: to assure the international community that States are complying with their non-proliferation and other peaceful undertakings; and to deter (a) the diversion of afeguarded nuclear materials to the production of nuclear explosives or for military purposes and (b) the misuse of safeguarded facilities with the aim of producing unsafeguarded nuclear material. It is clear that no international safeguards system can physically prevent diversion. The IAEA safeguards system is basically a verification measure designed to provide assurance in those cases in which diversion has not occurred. Verification is accomplished by two basic means: material accountancy and containment and surveillance measures. Nuclear material accountancy is the fundamental IAEA safeguards mechanism, while containment and surveillance serve as important complementary measures. Material accountancy refers to a collection of measurements and other determinations which enable the State and the Agency to maintain a current picture of the location and movement of nuclear material into and out of material balance areas, i. e. areas where all material entering or leaving is measurab e. A containment measure is one that is designed by taking advantage of structural characteristics, such as containers, tanks or pipes, etc. To establish the physical integrity of an area or item by preventing the undetected movement of nuclear material or equipment. Such measures involve the application of tamper-indicating or surveillance devices. Surveillance refers to both human and instrumental observation aimed at indicating the movement of nuclear material. The verification process consists of three over-lapping elements: (a) Provision by the State of information such as - design information describing nuclear installations; - accounting reports listing nuclear material inventories, receipts and shipments; - documents amplifying and clarifying reports, as applicable; - notification of international transfers of nuclear material. (b) Collection by the IAEA of information through inspection activities such as - verification of design information - examination of records and repo ts - measurement of nuclear material - examination of containment and surveillance measures - follow-up activities in case of unusual findings. (c) Evaluation of the information provided by the State and of that collected by inspectors to determine the completeness, accuracy and validity of the information provided by the State and to resolve any anomalies and discrepancies. To design an effective verification system, one must identify possible ways and means by which nuclear material could be diverted from peaceful uses, including means to conceal such diversions. These theoretical ways and means, which have become known as diversion strategies, are used as one of the basic inputs for the development of safeguards procedures, equipment and instrumentation. For analysis of implementation strategy purposes, it is assumed that non-compliance cannot be excluded a priori and that consequently there is a low but non-zero probability that a diversion could be attempted in all safeguards ituations. An important element of diversion strategies is the identification of various possible diversion paths; the amount, type and location of nuclear material involved, the physical route and conversion of the material that may take place, rate of removal and concealment methods, as appropriate. With regard to the physical route and conversion of nuclear material the following main categories may be considered: - unreported removal of nuclear material from an installation or during transit - unreported introduction of nuclear material into an installation - unreported transfer of nuclear material from one material balance area to another - unreported production of nuclear material, e. g. enrichment of uranium or production of plutonium - undeclared uses of the material within the installation. With respect to the amount of nuclear material that might be diverted in a given time (the diversion rate), the continuum between the following two limiting cases is cons dered: - one significant quantity or more in a short time, often known as abrupt diversion; and - one significant quantity or more per year, for example, by accumulation of smaller amounts each time to add up to a significant quantity over a period of one year, often called protracted diversion. Concealment methods may include: - restriction of access of inspectors - falsification of records, reports and other material balance areas - replacement of nuclear material, e. g. use of dummy objects - falsification of measurements or of their evaluation - interference with IAEA installed equipment.As a result of diversion and its concealment or other actions, anomalies will occur. All reasonable diversion routes, scenarios/strategies and concealment methods have to be taken into account in designing safeguards implementation strategies so as to provide sufficient opportunities for the IAEA to observe such anomalies. The safeguards approach for each facility will make a different use of these procedures, equipment and instrumentation according to the various diversion strategies which could be applicable to that facility and according to the detection and inspection goals which are applied. Postulated pathways sets of scenarios comprise those elements of diversion strategies which might be carried out at a facility or across a State's fuel cycle with declared or undeclared activities. All such factors, however, contain a degree of fuzziness that need a human judgment to make the ultimate conclusion that all material is being used for peaceful purposes. Safeguards has been traditionally based on verification of declared material and facilities using material accountancy as a fundamental measure. The strength of material accountancy is based on the fact that it allows to detect any diversion independent of the diversion route taken. Material accountancy detects a diversion after it actually happened and thus is powerless to physically prevent it and can only deter by the risk of early detection any contemplation by State authorities to carry out a diversion. Recently the IAEA has been faced with new challenges. To deal with these, various measures are being reconsidered to strengthen the safeguards system such as enhanced assessment of the completeness of the State's initial declaration of nuclear material and installations under its jurisdiction enhanced monitoring and analysis of open information and analysis of open information that may indicate inconsistencies with the State's safeguards obligations. Precise information vital for such enhanced assessments and analyses is normally not available or, if available, difficult and expensive collection of information would be necessary. Above all, realistic appraisal of truth needs sound human judgment.

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Effect of Noise on Density Differences of Tissue in Computed Tomography (컴퓨터 단층촬영의 조직간 밀도차이에 대한 노이즈 영향)

  • Yang, Won Seok;Son, Jung Min;Chon, Kwon Su
    • Journal of the Korean Society of Radiology
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    • v.12 no.3
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    • pp.403-407
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    • 2018
  • Currently, the highest cancer death rate in Korea is lung cancer, which is a typical cancer that is difficult to detect early. Low-dose chest CT is being used for early detection, which has a greater lung cancer diagnosis rate of about three times than regular chest x-ray images. However, low-dose chest CT not only significantly reduces image resolution but also has a weak signal and is sensitive to noise. Also, air filled lungs are low-density organs and the presence of noise can significantly affect early diagnosis of cancer. This study used Visual C++ to set a circle inside a large circle with a density of 2.0, with a density of 1.0, which is the density of water, in which five small circle of mathematics have different densities. Gaussian noise was generated by 1%, 2%, 3%, and 4% respectively to determine the effect of noise on the mean value, the standard deviation value, and the relative noise ratio(SNR). In areas where the density difference between the large and small circles was greatest in the event of 1 % noise, the SNR in the area with the greatest variation in noise was 4.669, and in areas with the lowest density difference, the SNR was 1.183. In addition, the SNR values can be seen to be high if the same results are obtained for both positive and negative densities. Quality was also clearly visible when the density difference was large, and if the noise level was increased, the SNR was reduced to significantly affect the noise. Low-density organs or organs in areas of similar density to cancers, will have significant noise effects, and the effects of density differences on the probability of noise will affect diagnosis.

Significance of Serum Ferritin in Multiple Trauma Patients with Acute Respiratory Distress Syndrome (다발성 외상 환자에서 발생되는 급성 호흡 곤란 증후군의 예측 인자로서 혈청 페리틴의 의의)

  • Ji, Yae-Sub;Kim, Nak-Hee;Jung, Ho-Geun;Ha, Dong-Yeup;Jung, Ki-Hoon
    • Journal of Trauma and Injury
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    • v.20 no.2
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    • pp.57-64
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    • 2007
  • Purpose: Clinically, acute respiratory distress syndrome (ARDS) occurs within 72 hours after acute exposure of risk factors. Because of its high fatality rate once ARDS progresses, early detection and management are essential to reduce the mortality rate. Accordingly, studies on early changes of ARDS were started, and serum ferritin, as well the as injury severity score (ISS), which has been addressed in previous studies, thought to be an early predictive indicator for ARDSMethods: From March 2003 to March 2005, we investigated 50 trauma patients who were admitted to the intensive care unit in Dongguk University Medical Center, Gyeongju. The patients were characterized according to age, sex, ISS, onset of ARDS, time onset of ARDS, serum ferritin level (posttraumatic $1^{st}\;&\;2^{nd}$ day), amount of transfused blood, and death. Abdominal computed topography was performed as an early diagnostic tool to evaluate the onset of ARDS according to its diagnostic criteria. The serum ferritin was measured by using a $VIDAS^{(R)}$ Ferritin (bioMeriux, Marcy-1' Etoile, France) kit with an enzyme-linked fluorescent assay method. For statistical analysis, Windows SPSS 13.0 and MedCalc were used to confirm the probability of obtaining a predictive measure from the receiver operating characteristics (ROC) curve. Results: The ISS varied from 14 to 66 (mean: 33.8) whereas the onset of ARDS could be predicted with the score above 30 (sensitivity: 90.0%, specificity: 60.0%, p<0.05). On the posttraumatic $1^{st}$ day, the serum ferritin levels were measured to be from 31 mg/dL to 1,200 mg/dL (mean: 456 mg/dL), and the onset of ARDS could be predicted when the value was over 340 mg/dL (sensitivity: 80.0%, specificity: 65.0%, p<0.05). On the posttraumatic $2^{nd}$ day, the serum ferritin levels were measured to be from 73 mg/dL to 1,200 mg/dL (mean: 404 mg/dL), and the onset of ARDS could be predicted when the value was over 627 mg/dL (sensitivity: 60.0%, specificity: 92.5%, p<0.05). The serum ferritin levels and the ISS were significantly higher on the posttraumatic $1^{st}$ and $2^{nd}$ day in the ARDS group, suggesting that they are suitable indices predicting the onset of ARDS, however relationship between the serum ferritin levels and the ISS was not statistically significant. Conclusion: In this study, we discovered increasing serum ferritin levels in multiple- trauma patients on the posttraumatic $1^{st}$ & $2^{nd}$ day and concluded that both the serum ferritin level and the ISS were good predictors of ARDS. Although they do not show statistically significant relationship to each other, they can be used as independent predictive measures for ARDS. Since ARDS causes high mortality, further studies, including the types of surgery and the methods of anesthesia on a large number of patients are essential to predict the chance of ARDS earlier and to reduce the incidence of death.

Change Detection of land-surface Environment in Gongju Areas Using Spatial Relationships between Land-surface Change and Geo-spatial Information (지표변화와 지리공간정보의 연관성 분석을 통한 공주지역 지표환경 변화 분석)

  • Jang Dong-Ho
    • Journal of the Korean Geographical Society
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    • v.40 no.3 s.108
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    • pp.296-309
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    • 2005
  • In this study, we investigated the change of future land-surface and relationships of land-surface change with geo-spatial information, using a Bayesian prediction model based on a likelihood ratio function, for analysing the land-surface change of the Gongju area. We classified the land-surface satellite images, and then extracted the changing area using a way of post classification comparison. land-surface information related to the land-surface change is constructed in a GIS environment, and the map of land-surface change prediction is made using the likelihood ratio function. As the results of this study, the thematic maps which definitely influence land-surface change of rural or urban areas are elevation, water system, population density, roads, population moving, the number of establishments, land price, etc. Also, thematic maps which definitely influence the land-surface change of forests areas are elevation, slope, population density, population moving, land price, etc. As a result of land-surface change analysis, center proliferation of old and new downtown is composed near Gum-river, and the downtown area will spread around the local roads and interchange areas in the urban area. In case of agricultural areas, a small tributary of Gum-river or an area of local roads which are attached with adjacent areas showed the high probability of change. Most of the forest areas are located in southeast and from this result we can guess why the wide chestnut-tree cultivation complex is located in these areas and the capability of forest damage is very high. As a result of validation using a prediction rate curve, a capability of prediction of urban area is $80\%$, agriculture area is $55\%$, forest area is $40\%$ in higher $10\%$ of possibility which the land-surface change would occur. This integration model is unsatisfactory to Predict the forest area in the study area and thus as a future work, it is necessary to apply new thematic maps or prediction models In conclusion, we can expect that this way can be one of the most essential land-surface change studies in a few years.

The NCAM Land-Atmosphere Modeling Package (LAMP) Version 1: Implementation and Evaluation (국가농림기상센터 지면대기모델링패키지(NCAM-LAMP) 버전 1: 구축 및 평가)

  • Lee, Seung-Jae;Song, Jiae;Kim, Yu-Jung
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.18 no.4
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    • pp.307-319
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    • 2016
  • A Land-Atmosphere Modeling Package (LAMP) for supporting agricultural and forest management was developed at the National Center for AgroMeteorology (NCAM). The package is comprised of two components; one is the Weather Research and Forecasting modeling system (WRF) coupled with Noah-Multiparameterization options (Noah-MP) Land Surface Model (LSM) and the other is an offline one-dimensional LSM. The objective of this paper is to briefly describe the two components of the NCAM-LAMP and to evaluate their initial performance. The coupled WRF/Noah-MP system is configured with a parent domain over East Asia and three nested domains with a finest horizontal grid size of 810 m. The innermost domain covers two Gwangneung deciduous and coniferous KoFlux sites (GDK and GCK). The model is integrated for about 8 days with the initial and boundary conditions taken from the National Centers for Environmental Prediction (NCEP) Final Analysis (FNL) data. The verification variables are 2-m air temperature, 10-m wind, 2-m humidity, and surface precipitation for the WRF/Noah-MP coupled system. Skill scores are calculated for each domain and two dynamic vegetation options using the difference between the observed data from the Korea Meteorological Administration (KMA) and the simulated data from the WRF/Noah-MP coupled system. The accuracy of precipitation simulation is examined using a contingency table that is made up of the Probability of Detection (POD) and the Equitable Threat Score (ETS). The standalone LSM simulation is conducted for one year with the original settings and is compared with the KoFlux site observation for net radiation, sensible heat flux, latent heat flux, and soil moisture variables. According to results, the innermost domain (810 m resolution) among all domains showed the minimum root mean square error for 2-m air temperature, 10-m wind, and 2-m humidity. Turning on the dynamic vegetation had a tendency of reducing 10-m wind simulation errors in all domains. The first nested domain (7,290 m resolution) showed the highest precipitation score, but showed little advantage compared with using the dynamic vegetation. On the other hand, the offline one-dimensional Noah-MP LSM simulation captured the site observed pattern and magnitude of radiative fluxes and soil moisture, and it left room for further improvement through supplementing the model input of leaf area index and finding a proper combination of model physics.

A Study on Particulate Matter Forecasting Improvement by using Asian Dust Emissions in East Asia (황사배출량을 적용한 동아시아 미세먼지 예보 개선 연구)

  • Choi, Daeryun;Yun, Huiyoung;Chang, Limseok;Lee, Jaebum;Lee, Younghee;Myoung, Jisu;Kim, Taehee;Koo, Younseo
    • Journal of the Korean Society of Urban Environment
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    • v.18 no.4
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    • pp.531-546
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    • 2018
  • Air quality forecasting system with Asian dust emissions was developed in East Asia, and $PM_{10}$ forecasting performance of chemical transport model with Asian dust emissions was validated and evaluated. The chemical transport model (CTM) with Asian dust emission was found to supplement $PM_{10}$ concentrations that had been under-estimated in China regions and improved statistics for performance of CTM, although the model were overestimated during some periods in China. In Korea, the prediction model adequately simulated inflow of Asian dust events on February 22~24 and March 16~17, but the model is found to be overestimated during no Asian dust event periods on April. However, the model supplemented $PM_{10}$ concentrations, which was underestimated in most regions in Korea and the statistics for performance of the models were improved. The $PM_{10}$ forecasting performance of air quality forecasting model with Asian dust emissions tends to improve POD (Probability of Detection) compared to basic model without Asian dust emissions, but A (Accuracy) has shown similar or decreased, and FAR (False Alarms) have increased during 2017.Therefore, the developed air quality forecasting model with Asian dust emission was not proposed as a representative $PM_{10}$ forecast model in South Korea.

A Case Study: Improvement of Wind Risk Prediction by Reclassifying the Detection Results (풍해 예측 결과 재분류를 통한 위험 감지확률의 개선 연구)

  • Kim, Soo-ock;Hwang, Kyu-Hong
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.23 no.3
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    • pp.149-155
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    • 2021
  • Early warning systems for weather risk management in the agricultural sector have been developed to predict potential wind damage to crops. These systems take into account the daily maximum wind speed to determine the critical wind speed that causes fruit drops and provide the weather risk information to farmers. In an effort to increase the accuracy of wind risk predictions, an artificial neural network for binary classification was implemented. In the present study, the daily wind speed and other weather data, which were measured at weather stations at sites of interest in Jeollabuk-do and Jeollanam-do as well as Gyeongsangbuk- do and part of Gyeongsangnam- do provinces in 2019, were used for training the neural network. These weather stations include 210 synoptic and automated weather stations operated by the Korean Meteorological Administration (KMA). The wind speed data collected at the same locations between January 1 and December 12, 2020 were used to validate the neural network model. The data collected from December 13, 2020 to February 18, 2021 were used to evaluate the wind risk prediction performance before and after the use of the artificial neural network. The critical wind speed of damage risk was determined to be 11 m/s, which is the wind speed reported to cause fruit drops and damages. Furthermore, the maximum wind speeds were expressed using Weibull distribution probability density function for warning of wind damage. It was found that the accuracy of wind damage risk prediction was improved from 65.36% to 93.62% after re-classification using the artificial neural network. Nevertheless, the error rate also increased from 13.46% to 37.64%, as well. It is likely that the machine learning approach used in the present study would benefit case studies where no prediction by risk warning systems becomes a relatively serious issue.

Analysis of Twitter for 2012 South Korea Presidential Election by Text Mining Techniques (텍스트 마이닝을 이용한 2012년 한국대선 관련 트위터 분석)

  • Bae, Jung-Hwan;Son, Ji-Eun;Song, Min
    • Journal of Intelligence and Information Systems
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    • v.19 no.3
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    • pp.141-156
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    • 2013
  • Social media is a representative form of the Web 2.0 that shapes the change of a user's information behavior by allowing users to produce their own contents without any expert skills. In particular, as a new communication medium, it has a profound impact on the social change by enabling users to communicate with the masses and acquaintances their opinions and thoughts. Social media data plays a significant role in an emerging Big Data arena. A variety of research areas such as social network analysis, opinion mining, and so on, therefore, have paid attention to discover meaningful information from vast amounts of data buried in social media. Social media has recently become main foci to the field of Information Retrieval and Text Mining because not only it produces massive unstructured textual data in real-time but also it serves as an influential channel for opinion leading. But most of the previous studies have adopted broad-brush and limited approaches. These approaches have made it difficult to find and analyze new information. To overcome these limitations, we developed a real-time Twitter trend mining system to capture the trend in real-time processing big stream datasets of Twitter. The system offers the functions of term co-occurrence retrieval, visualization of Twitter users by query, similarity calculation between two users, topic modeling to keep track of changes of topical trend, and mention-based user network analysis. In addition, we conducted a case study on the 2012 Korean presidential election. We collected 1,737,969 tweets which contain candidates' name and election on Twitter in Korea (http://www.twitter.com/) for one month in 2012 (October 1 to October 31). The case study shows that the system provides useful information and detects the trend of society effectively. The system also retrieves the list of terms co-occurred by given query terms. We compare the results of term co-occurrence retrieval by giving influential candidates' name, 'Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn' as query terms. General terms which are related to presidential election such as 'Presidential Election', 'Proclamation in Support', Public opinion poll' appear frequently. Also the results show specific terms that differentiate each candidate's feature such as 'Park Jung Hee' and 'Yuk Young Su' from the query 'Guen Hae Park', 'a single candidacy agreement' and 'Time of voting extension' from the query 'Jae In Moon' and 'a single candidacy agreement' and 'down contract' from the query 'Chul Su Ahn'. Our system not only extracts 10 topics along with related terms but also shows topics' dynamic changes over time by employing the multinomial Latent Dirichlet Allocation technique. Each topic can show one of two types of patterns-Rising tendency and Falling tendencydepending on the change of the probability distribution. To determine the relationship between topic trends in Twitter and social issues in the real world, we compare topic trends with related news articles. We are able to identify that Twitter can track the issue faster than the other media, newspapers. The user network in Twitter is different from those of other social media because of distinctive characteristics of making relationships in Twitter. Twitter users can make their relationships by exchanging mentions. We visualize and analyze mention based networks of 136,754 users. We put three candidates' name as query terms-Geun Hae Park', 'Jae In Moon', and 'Chul Su Ahn'. The results show that Twitter users mention all candidates' name regardless of their political tendencies. This case study discloses that Twitter could be an effective tool to detect and predict dynamic changes of social issues, and mention-based user networks could show different aspects of user behavior as a unique network that is uniquely found in Twitter.