• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.2
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• pp.174-189
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• 2015

The objective of this study was to reconstruct spatial information using the results of the investigation and evaluation of the health of the living organisms, habitat, and water quality at the investigation points for the aquatic ecosystem health of the Nakdong River basin, to support the rational decision making of the aquatic ecosystem preservation and restoration policies of the Nakdong River basin using spatial analysis techniques, and to present efficient management methods. To analyze the aquatic ecosystem health of the Nakdong River basin, punctiform data were constructed based on the position information of each point with the aquatic ecosystem health investigation and evaluation results of 250 investigation sections. To apply the spatial analysis technique, the data need to be reconstructed into areal data. For this purpose, spatial influence and trends were analyzed using the Kriging interpolation(ArcGIS 10.1, Geostatistical Analysis), and were reconstructed into areal data. To analyze the spatial distribution characteristics of the Nakdong River basin health based on these analytical results, hotspot(Getis-Ord Gi, $G^*_i$), LISA(Local Indicator of Spatial Association), and standard deviational ellipse analyses were used. The hotspot analysis results showed that the hotspot basins of the biotic indices(TDI, BMI, FAI) were the Andong Dam upstream, Wangpicheon, and the Imha Dam basin, and that the health grades of their biotic indices were good. The coldspot basins were Nakdong River Namhae, the Nakdong River mouth, and the Suyeong River basin. The LISA analysis results showed that the exceptional areas were Gahwacheon, the Hapcheon Dam, and the Yeong River upstream basin. These areas had high bio-health indices, but their surrounding basins were low and required management for aquatic ecosystem health. The hotspot basins of the physicochemical factor(BOD) were the Nakdong River downstream basin, Suyeong River, Hoeya River, and the Nakdong River Namhae basin, whereas the coldspot basins were the upstream basins of the Nakdong River tributaries, including Andong Dam, Imha Dam, and Yeong River. The hotspots of the habitat and riverside environment factor(HRI) were different from the hotspots and coldspots of each factor in the LISA analysis results. In general, the habitat and riverside environment of the Nakdong River mainstream and tributaries, including the Nakdong river upstream, Andong Dam, Imha Dam, and the Hapcheon Dam basin, had good health. The coldspot basins of the habitat and riverside environment also showed low health indices of the biotic indices and physicochemical factors, thus requiring management of the habitat and riverside environment. As a result of the time-series analysis with a standard deviation ellipsoid, the areas with good aquatic ecosystem health of the organisms, habitat, and riverside environment showed a tendency to move northward, and the BOD results showed different directions and concentrations by the year of investigation. These aquatic ecosystem health analysis results can provide not only the health management information for each investigation spot but also information for managing the aquatic ecosystem in the catchment unit for the working research staff as well as for the water environment researchers in the future, based on spatial information.

• Nuclear Medicine and Molecular Imaging
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• v.41 no.3
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• pp.234-240
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• 2007

Purpose: In this study we propose a block-iterative method for reconstructing Compton scattered data. This study shows that the well-known expectation maximization (EM) approach along with its accelerated version based on the ordered subsets principle can be applied to the problem of image reconstruction for Compton camera. This study also compares several methods of constructing subsets for optimal performance of our algorithms. Materials and Methods: Three reconstruction algorithms were implemented; simple backprojection (SBP), EM, and ordered subset EM (OSEM). For OSEM, the projection data were grouped into subsets in a predefined order. Three different schemes for choosing nonoverlapping subsets were considered; scatter angle-based subsets, detector position-based subsets, and both scatter angle- and detector position-based subsets. EM and OSEM with 16 subsets were performed with 64 and 4 iterations, respectively. The performance of each algorithm was evaluated in terms of computation time and normalized mean-squared error. Results: Both EM and OSEM clearly outperformed SBP in all aspects of accuracy. The OSEM with 16 subsets and 4 iterations, which is equivalent to the standard EM with 64 iterations, was approximately 14 times faster in computation time than the standard EM. In OSEM, all of the three schemes for choosing subsets yielded similar results in computation time as well as normalized mean-squared error. Conclusion: Our results show that the OSEM algorithm, which have proven useful in emission tomography, can also be applied to the problem of image reconstruction for Compton camera. With properly chosen subset construction methods and moderate numbers of subsets, our OSEM algorithm significantly improves the computational efficiency while keeping the original quality of the standard EM reconstruction. The OSEM algorithm with scatter angle- and detector position-based subsets is most available.

• The Korean Journal of Nuclear Medicine
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• v.39 no.4
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• pp.252-256
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• 2005

Purpose: Thyroglobulin (Tg) is a valuable and sensitive tool as a marker for diagnosis and follow-up for several thyroid disorders, especially, in the follow-up of patients with differentiated thyroid cancer (DTC). Often, clinical decisions rely entirely on the serum Tg concentration. But the Tg assay is one of the most challenging laboratory measurements to perform accurately owing to antithyroglobulin antibody (Anti-Tg). In this study, we have compared the degree of Anti-Tg effects on the measurement of Tg between availale Tg measuring kits. Materials and Methods: Measurement of Tg levels for standard Tg solution was performed with two different kits commercially available (A/B kits) using immunoradiometric assay technique either with absence or presence of three different concentrations of Anti-Tg. Measurement of Tg for patient's serum was also performed with the same kits. Patient's serum samples were prepared with mixtures of a serum containing high Tg levels and a serum containg high Anti-Tg concentrations. Results: In the measurements of standard Tg solution, presence of Anti-Tg resulted in falsely lower Tg level by both A and B kits. Degree of Tg underestimation by h kit was more prominent than B kit. The degree of underestimation by B kit was trivial therefore clinically insignificant, but statistically significant. Addition of Anti-Tg to patient serum resulted in falsely lower Tg levels with only A kit. Conclusion: Tg level could be underestimated in the presence of anti-Tg. Anti-Tg effect on Tg measurement was variable according to assay kit used. Therefore, accuracy test must be performed for individual Tg-assay kit.

• Nuclear Medicine and Molecular Imaging
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• v.42 no.5
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• pp.383-393
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• 2008

Purpose: Cancer specific killing can be achieved by therapeutic gene activated by cancer specific promotor. Expression of sodium iodide symporter (NIS) gene causes transportation and concentration of iodide into the cell, therefore radioiodine treatment after NIS gene transfer to cancer cell could be a form of radionuclide gene therapy. luciferase (Luc) gene transfected cancer cell can be monitored by in vivo optical imaging after D-luciferin injection. Aims of the study are to make vector with both therapeutic NIS gene driven by AFP promoter and reporter Luc gene driven by CMV promoter, to perform hepatocellular carcinoma specific radiodiodine gene therapy by the vector, and assessment of the therapy effect by optical imaging using luciferase expression. Materials and Methods: A Vector with AFP promoter driven NIS gene and CMV promoter driven Luc gene (AFP-NIS-CMV-Luc) was constructed. Liver cancer cell (HepG2, Huh-7) and non liver cancer cell (HCT-15) were transfected with the vector using liposome. Expression of the NIS gene at mRNA level was elucidated by RT-PCR. Radioiodide uptake, perchlorate blockade, and washout tests were performed and bioluminescence also measured by luminometer in these cells. In vitro clonogenic assay with 1-131 was performed. In vivo nuclear imaging was obtained with gamma camera after 1-131 intraperitoneal injection. Results: A Vector with AFP-NIS-CMV-Luc was constructed and successfully transfected into HepG2, Huh-7 and HCT-15 cells. HepG2 and Huh-7 cells with AFP-NIS-CMV-Luc gene showed higher iodide uptake than non transfected cells and the higher iodide uptake was totally blocked by addition of perchlorate. HCT-15 cell did not showed any change of iodide uptake by the gene transfection. Transfected cells had higher light output than control cells. In vitro clonogenic assay, transfected HepG2 and Huh-7 cells showed lower colony count than non transfected HepG2 and Huh-7 cells, but transfected HCT-15 cell did not showed any difference than non transfected HCT-15 cell. Number of Huh-7 cells with AFP-NIS-CMV-Luc gene transfection was positively correlated with radioidine accumulation and luciferase activity. In vivo nuclear imaging with 1-131 was successful in AFP-NIS-CMV-Luc gene transfected Huh-7 cell xenograft on nude mouse. Conclusion: A Vector with AFP promoter driven NIS and CMV promoter driven Luc gene was constructed. Transfection of the vector showed liver cancer cell specific enhancement of 1-131 cytotoxicity by AFP promoter, and the effect of the radioiodine therapy can be successfully assessed by non-invasive luminescence measurement.

• Nuclear Medicine and Molecular Imaging
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• v.41 no.4
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• pp.291-298
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• 2007

Purpose: To investigate the feasibility of TI-201 SPECT with intra coronary injection (lC-I) in the detection of viable myocardium, we have performed SPECT imaging after direct intracoronary injection of TI-201 and images were compared with those of stress-reinjection (Re-I) SPECT. Methods: Fourteen coronary artery disease patients (male 11, mean age 54 years) who had myocardial infarction or demonstrated left ventricular wall motion abnormality on echocardiography were enrolled. Three mCi of TI-201 was injected into both coronary arteries during angiography and images were acquired between 6- and 24-hour after injection. Reinjection imaging with 1 mCi of TI-201 was performed at 4-hour after adenosine stress imaging with 3 mCi of TI-201. Images were interpreted according to 4-grade visual scoring system (grade 0-3). Segments with mild to moderated uptake (${\leq}$grade 1), and upgraded more than one score with reinjection, and were defined as viable myocardium. Results: Image quality was poor in two cases with IC-I. Numbers of non-viable segments were 60 (23.8%) with IC-I, and 38 (15.1%) with Re-I, respectively. Overall agreement for perfusion grade per myocardial segment in each IC-I and Re-I was 76.5%. Overall agreement for viable segment between IC-I and Re-I was 90.5%. Only one out of 38 segments interpreted as non-viable with Re-I were interpretated as viable with IC-I. And 23 out of 214 segments interpreted as viable with Re-I were interpreted as non-viable with IC-I. Conclusion: Intracoronary TI-201 SPECT seemed to be not advantageous over stress-rest reinjection imaging in the assessment of myocardial viability, mainly due to low count statistics at 6-hour or 24-hour delayed time points. The feasibility of intracoronary TI- 201 SPECT is considered to be limited.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.73-92
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• 2014

An Adaptive Clustering-based Collaborative Filtering Technique was proposed to solve the fundamental problems of collaborative filtering, such as cold-start problems, scalability problems and data sparsity problems. Previous collaborative filtering techniques were carried out according to the recommendations based on the predicted preference of the user to a particular item using a similar item subset and a similar user subset composed based on the preference of users to items. For this reason, if the density of the user preference matrix is low, the reliability of the recommendation system will decrease rapidly. Therefore, the difficulty of creating a similar item subset and similar user subset will be increased. In addition, as the scale of service increases, the time needed to create a similar item subset and similar user subset increases geometrically, and the response time of the recommendation system is then increased. To solve these problems, this paper suggests a collaborative filtering technique that adapts a condition actively to the model and adopts the concepts of a context-based filtering technique. This technique consists of four major methodologies. First, items are made, the users are clustered according their feature vectors, and an inter-cluster preference between each item cluster and user cluster is then assumed. According to this method, the run-time for creating a similar item subset or user subset can be economized, the reliability of a recommendation system can be made higher than that using only the user preference information for creating a similar item subset or similar user subset, and the cold start problem can be partially solved. Second, recommendations are made using the prior composed item and user clusters and inter-cluster preference between each item cluster and user cluster. In this phase, a list of items is made for users by examining the item clusters in the order of the size of the inter-cluster preference of the user cluster, in which the user belongs, and selecting and ranking the items according to the predicted or recorded user preference information. Using this method, the creation of a recommendation model phase bears the highest load of the recommendation system, and it minimizes the load of the recommendation system in run-time. Therefore, the scalability problem and large scale recommendation system can be performed with collaborative filtering, which is highly reliable. Third, the missing user preference information is predicted using the item and user clusters. Using this method, the problem caused by the low density of the user preference matrix can be mitigated. Existing studies on this used an item-based prediction or user-based prediction. In this paper, Hao Ji's idea, which uses both an item-based prediction and user-based prediction, was improved. The reliability of the recommendation service can be improved by combining the predictive values of both techniques by applying the condition of the recommendation model. By predicting the user preference based on the item or user clusters, the time required to predict the user preference can be reduced, and missing user preference in run-time can be predicted. Fourth, the item and user feature vector can be made to learn the following input of the user feedback. This phase applied normalized user feedback to the item and user feature vector. This method can mitigate the problems caused by the use of the concepts of context-based filtering, such as the item and user feature vector based on the user profile and item properties. The problems with using the item and user feature vector are due to the limitation of quantifying the qualitative features of the items and users. Therefore, the elements of the user and item feature vectors are made to match one to one, and if user feedback to a particular item is obtained, it will be applied to the feature vector using the opposite one. Verification of this method was accomplished by comparing the performance with existing hybrid filtering techniques. Two methods were used for verification: MAE(Mean Absolute Error) and response time. Using MAE, this technique was confirmed to improve the reliability of the recommendation system. Using the response time, this technique was found to be suitable for a large scaled recommendation system. This paper suggested an Adaptive Clustering-based Collaborative Filtering Technique with high reliability and low time complexity, but it had some limitations. This technique focused on reducing the time complexity. Hence, an improvement in reliability was not expected. The next topic will be to improve this technique by rule-based filtering.

• Tuberculosis and Respiratory Diseases
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• v.45 no.5
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• pp.1058-1066
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• 1998

Background: Actinomycotic infection is uncommon and primary actinomycosis of the lung and chest wall has been less frequently reported. This disease may present as chronic debilitating illness with radiologic manifestation simulating lung tumor, pulmonary infiltrating lesion, or chronic suppuration. Diagnosis of choice was not definded yet and role of bronchoscopy on diagnosis was not described yet. Methods: From 1989 to 1998, we experienced 17 cases of thoracic actinomycosis. We have reviewed the case notes of 17 patients with thoracic actinomycosis. The mean age at presentation was $53{\pm}13$ years, 11 were male. Results: Cough, hemoptysis, sputum production, chest pain and weight loss were the commonest symptoms. The mean delay between presentation and diagnosis was $6.6{\pm}7.8$ months. There were six patients who presented with a clinical picture of a suppurative lesion and eleven patients were suspected of having primary lung tumor initially. In no cases was made an accurate diagnosis at the time of hospital admission. Associated diseases were emphysema (1 case), bronchiectasis (2 cases) and tuberculosis (2 cases). Bronchoscopic findings were mucosal swelling and stenosis(n=4), mucosal swelling, stenosis and necrotic covering (n=2), mass (n=3), mass and necrotic covering (n=1) and normal(n=6). Radiologic findings were mass lesion(n=8), pneumonitis(n=3), atelectasis(n=3), pleural effusion(n=2), and normal(n=3). Final diagnosis was based on percutaneous needle aspiration and biopsy (n=3), bronchoscopic biopsy specimens (n=9), mediastinoscopic biopsy (n=1) and histologic examination of resected tissue in the remaining patients(n=4) who received surgical excision. Among 17 patients, 13 were treated medically and the other 4 received surgical intervention followed by antibiotic treatment. Regarding the surgically treated patients, suspected malignancy is the most common indication for operation. However. both medically and surgically treated patients achieved good clinical results. Conclusion: Thoracic actinomycosis is rare. but should still be considered in the differential diagnosis of a chrinic, localized pulmonary lesion. Thoracic actinomycosis may co-exist with pulmonary tuberculosis or lung cancer. If the lesion is located in the central of the lung. the bronchoscopy is recommanded for the diagnosis.

• The Korean Journal of Nuclear Medicine
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• v.38 no.6
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• pp.486-491
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• 2004

Purpose: factor analysis and independent component analysis (ICA) has been used for handling dynamic image sequences. Theoretical advantages of a newly suggested ICA method, ensemble ICA, leaded us to consider applying this method to the analysis of dynamic myocardial $H_2^{15}O$ PET data. In this study, we quantified patients' blood flow using the ensemble ICA method. Materials and Methods: Twenty subjects underwent $H_2^{15}O$ PET scans using ECAT EXACT 47 scanner and myocardial perfusion SPECT using Vertex scanner. After transmission scanning, dynamic emission scans were initiated simultaneously with the injection of $555{\sim}740$ MBq $H_2^{15}O$. Hidden independent components can be extracted from the observed mixed data (PET image) by means of ICA algorithms. Ensemble learning is a variational Bayesian method that provides an analytical approximation to the parameter posterior using a tractable distribution. Variational approximation forms a lower bound on the ensemble likelihood and the maximization of the lower bound is achieved through minimizing the Kullback-Leibler divergence between the true posterior and the variational posterior. In this study, posterior pdf was approximated by a rectified Gaussian distribution to incorporate non-negativity constraint, which is suitable to dynamic images in nuclear medicine. Blood flow was measured in 9 regions - apex, four areas in mid wall, and four areas in base wall. Myocardial perfusion SPECT score and angiography results were compared with the regional blood flow. Results: Major cardiac components were separated successfully by the ensemble ICA method and blood flow could be estimated in 15 among 20 patients. Mean myocardial blood flow was $1.2{\pm}0.40$ ml/min/g in rest, $1.85{\pm}1.12$ ml/min/g in stress state. Blood flow values obtained by an operator in two different occasion were highly correlated (r=0.99). In myocardium component image, the image contrast between left ventricle and myocardium was 1:2.7 in average. Perfusion reserve was significantly different between the regions with and without stenosis detected by the coronary angiography (P<0.01). In 66 segment with stenosis confirmed by angiography, the segments with reversible perfusion decrease in perfusion SPECT showed lower perfusion reserve values in $H_2^{15}O$ PET. Conclusions: Myocardial blood flow could be estimated using an ICA method with ensemble learning. We suggest that the ensemble ICA incorporating non-negative constraint is a feasible method to handle dynamic image sequence obtained by the nuclear medicine techniques.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.137-154
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• 2018

Animal infectious diseases, such as avian influenza and foot and mouth disease, occur almost every year and cause huge economic and social damage to the country. In order to prevent this, the anti-quarantine authorities have tried various human and material endeavors, but the infectious diseases have continued to occur. Avian influenza is known to be developed in 1878 and it rose as a national issue due to its high lethality. Food and mouth disease is considered as most critical animal infectious disease internationally. In a nation where this disease has not been spread, food and mouth disease is recognized as economic disease or political disease because it restricts international trade by making it complex to import processed and non-processed live stock, and also quarantine is costly. In a society where whole nation is connected by zone of life, there is no way to prevent the spread of infectious disease fully. Hence, there is a need to be aware of occurrence of the disease and to take action before it is distributed. Epidemiological investigation on definite diagnosis target is implemented and measures are taken to prevent the spread of disease according to the investigation results, simultaneously with the confirmation of both human infectious disease and animal infectious disease. The foundation of epidemiological investigation is figuring out to where one has been, and whom he or she has met. In a data perspective, this can be defined as an action taken to predict the cause of disease outbreak, outbreak location, and future infection, by collecting and analyzing geographic data and relation data. Recently, an attempt has been made to develop a prediction model of infectious disease by using Big Data and deep learning technology, but there is no active research on model building studies and case reports. KT and the Ministry of Science and ICT have been carrying out big data projects since 2014 as part of national R &D projects to analyze and predict the route of livestock related vehicles. To prevent animal infectious diseases, the researchers first developed a prediction model based on a regression analysis using vehicle movement data. After that, more accurate prediction model was constructed using machine learning algorithms such as Logistic Regression, Lasso, Support Vector Machine and Random Forest. In particular, the prediction model for 2017 added the risk of diffusion to the facilities, and the performance of the model was improved by considering the hyper-parameters of the modeling in various ways. Confusion Matrix and ROC Curve show that the model constructed in 2017 is superior to the machine learning model. The difference between the2016 model and the 2017 model is that visiting information on facilities such as feed factory and slaughter house, and information on bird livestock, which was limited to chicken and duck but now expanded to goose and quail, has been used for analysis in the later model. In addition, an explanation of the results was added to help the authorities in making decisions and to establish a basis for persuading stakeholders in 2017. This study reports an animal infectious disease prevention system which is constructed on the basis of hazardous vehicle movement, farm and environment Big Data. The significance of this study is that it describes the evolution process of the prediction model using Big Data which is used in the field and the model is expected to be more complete if the form of viruses is put into consideration. This will contribute to data utilization and analysis model development in related field. In addition, we expect that the system constructed in this study will provide more preventive and effective prevention.