• Journal of Korean Society for Atmospheric Environment
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• v.24 no.2
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• pp.162-175
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• 2008

Gyeongju, which was the central city of the ancient civilization at Silla Kingdom, has various kinds of stone cultural properties. It is significantly important to preserve historical sources of Korea. However, recent air quality data measured in Gyeongju did not show good air quality level. In order to investigate variation of the concentration of the air pollutants with meteorological condition, an air quality monitoring and an aerosol sampling were conducted during the intensive monitoring period in Gyeongju. Impacts of the meteorological factors on the air pollutants were also analyzed based on the air mass pathway categories using HYSPLIT model and the local wind patterns using MM5 model. The prevailing air mass pathways were classified into four categories as following; category I affected by easterly marine aerosols, category II affected by northwesterly continental aerosols, category III affected by southwesterly continental aerosols, and category IV affected by northerly continental aerosols. The concentrations of the air quality standards were relatively lower during the fall intensive monitoring period. At that time, the easterly marine air mass pattern was dominated. The seasonal average mass concentration of $PM_{10,Opt}$, which optically measured at the monitoring site, was the highest value of $77.6{\pm}28.3\;{\mu}g\;m^{-3}$ during the spring intensive monitoring period but the lowest value of $20.1{\pm}5.3\;{\mu}g\;m^{-3}$ during the fall intensive monitoring period. The concentrations of $SO_2$ and CO were relatively higher when the air mass came from the northwestern continent or the northern continent. The concentrations of ${SO_4}^{2-}$ and ${NO_3}^-$ increased under the northwesterly continental condition. It was estimated that the acidic aerosols were dominated in the atmosphere of Gyeongju when the air mass came from the continental regions.

• Journal of KIISE:Software and Applications
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• v.32 no.7
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• pp.674-682
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• 2005

This paper proposes classification of multi-spectral satellite image based on fusion of fuzzy G-K (Gustafson-Kessel) algorithm and PCM algorithm. The suggested algorithm establishes the initial cluster centers by selecting training data from each category, and then executes the fuzzy G-K algorithm. PCM algorithm perform using classification result of the fuzzy G-K algorithm. The classification categories are allocated to the corresponding category when the results of classification by fuzzy G-K algorithm and PCM algorithm belong to the same category. If the classification result of two algorithms belongs to the different category, the pixels are allocated by Bayesian maximum likelihood algorithm. Bayesian maximum likelihood algorithm uses the data from the interior of the average intracluster distance. The information of the pixels within the average intracluster distance has a positive normal distribution. It improves classification result by giving a positive effect in Bayesian maximum likelihood algorithm. The proposed method is applied to IKONOS and Landsat TM remote sensing satellite image for the test. As a result, the overall accuracy showed a better outcome than individual Fuzzy G-K algorithm and PCM algorithm or the conventional maximum likelihood classification algorithm.

• Journal of Korean Medical classics
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• v.35 no.4
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• pp.77-96
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• 2022

Objectives : This paper examines the medical treatise and treatment methods of Zhang Jiebin on the depressive pattern, for clinical application today. Methods : The Zazhengmo/Yuzheng chapter of the Jingyue Quanshu, related texts and annotations of the Huangdineijing, and related contents among the medical texts of the JinYuan masters were analyzed. Developmental process of the medical theories were compared and examined. Results : Zhang focused on the mechanism in which emotion affects Qi leading to a disease state, and categorized Yu[鬱, depressed state] into three: anger depression, contemplative depression and comprehensive depression. The concept of the Five Depressive Patterns and its treatment from the Huangdineijing·Suwen which was considered as excess pattern was expanded to include deficiency pattern based on comparison with annotations of Wangbing, Hwashou, and Wang Andao. Treatment methods centered on purging was also expanded to include tonifying to restore the damaged Jing Qi. The depressive patterns anger depression, contemplative depression and comprehensive depression were subdivided according to excess and deficiency, for which formulas such as Shenxiangsan, Shoupijian, Guipitang were suggested. As the depressive pattern is caused by emotions and thus the Heart, the Yiqingbianqi method that directly deals with emotions was suggested. Zhang adopted Zhu Zhenheng's opinion which expands the category of Yu, and in the perspective of excess/deficiency, it is most similar to that of Li Dongyuan. Conclusions : Before Zhang, the depressive pattern was discussed in terms of it being excess pattern. However, Zhang's discussion on depressive pattern based on anger depression, contemplative depression and comprehensive depression focuses on emotional stagnation while suggesting the possibility of deficient stagnation, expanding previous understanding. In terms of treatment, tonifying methods for deficiency pattern was added, while consideration of emotion itself became necessary in treatment.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.2
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• pp.238-243
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• 2007

The TAM(Topographic Attentive Mapping) network neural network model is an especially effective one for pattern analysis. It is composed of of Input layer, category layer, and output layer. Fuzzy rule, lot input and output data are acquired from it. The TAM network with three pruning rules for reducing links and nodes at the layer is called fuzzy TAM network. In this paper, we apply fuzzy TAM network to pattern analysis of leadership type for organizational leader and show its usefulness. Here, criteria of input layer and target value of output layer are the value and leadership related personality type variables of the Egogram and Enneagram, respectively.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.1
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• pp.86-93
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• 2006

The TAM(Topographic Attentive Mapping) network based on a biologically-motivated neural network model is an especially effective one for pattern analysis. It is composed of of input layer, category layer, and output layer. Fuzzy rule, for input and output data are acquired from it. The TAM network with three pruning rules for reducing links and nodes at the layer is called fuzzy TAM network. In this paper, we apply fuzzy TAM network to pattern analysis of core competency model for subcontractors of construction companies and show its usefulness.

• Phonetics and Speech Sciences
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• v.9 no.4
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• pp.99-106
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• 2017

Clinical data about vocal nodules have seldom been reported, even though vocal nodules are commonly diagnosed in outpatient speech and voice clinic. This study aims to investigate clinical characteristics of the patients who are diagnosed with vocal nodules. This study analyzed the data for 10 years from the 319 patients diagnosed with vocal nodules (45 males and 274 females with the mean age of 39.4 ranging from 2 to 83) in terms of gender, age, occupation, voice change initiation pattern, change with time, throat clearing, smoking history, type of voice abuse, acoustic analysis, maximum phonation time, GRBAS, and VHI. Thirteen patients (4.08%) had unilateral vocal nodule and 306 patients (95.9%) had bilateral vocal nodule, the majority of which had a pattern of asymmetry (73.9%). The glottal closure pattern was hourglass in 72.1% of patients, posterior chink in 17.9% of patients, and irregular in 7.9% of patients. The most common occupational category was professional voice users (43.4%). The voice abuse pattern included excessive talking in 96 patients (76.8%), loud voice in 78 (62.4%) patients, and excessive singing in 17 patients (21.6%). The patients showed worse scores in G, B, and S than in R and A for the GRBAS evaluation. The most recommended treatment for vocal nodules was voice therapy. The current clinical data will be helpful for treatment planning for the patients of vocal nodule.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.1
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• pp.54-61
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• 2009

This paper presents a new electromyogram (EMG) pattern recognition method based on the Hierarchical Temporal Memory (HTM) algorithm which is originally devised for image pattern recognition. In the modified HTM algorithm, a simplified two-level structure with spatial pooler, temporal pooler, and supervised mapper is proposed for efficient learning and classification of the EMG signals. To enhance the recognition performance, the category information is utilized not only in the supervised mapper but also in the temporal pooler. The experimental results show that the ten kinds of hand motion are successfully recognized.

• Journal of radiological science and technology
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• v.45 no.4
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• pp.341-346
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• 2022

The color overlay pattern of thyroid shear wave elastography applied in this study distinguishes benign and malignant nodules based on the optimal cut-off value of 74.2 kPa. From august 2021 to september 2021, thyroid ultrasound and elastography were performed on 57 patients with thyroid lesions using an ultrasound device RS85 prestige (Samsung Medison, Korea) and a 2-14 MHz linear transducer. In addition, the results of classification by K-TIRADS for each thyroid nodule and the results of classification by color overlay pattern according to the kPa value of acoustic ultrasound were compared and analyzed. In the color overlay pattern, the results classified as 40 people from dark blue to light blue and 17 people from green to red were similar to the K-TIRADS category results, which were classified as 42 benign and 15 malignant. Between blue and light blue, benign, and between green and red, malignant. If the shear wave elastography method is applied before the fine-needle aspiration cytology of the thyroid nodule is performed, the differential diagnosis of thyroid tissue from benign and malignant can be predicted in advance, and it will help to reduce unnecessary invasive tests.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.05a
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• pp.338-341
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• 2003

TIn this study, by formulating input layer, category later, and output layer from data, and in using TAM(Topographic Attentive Mapping) network that created fuzzy rule, it categorized into companies went bankrupt with finances in the black figures, and in the red figures.

• ETRI Journal
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• v.43 no.2
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• pp.272-287
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• 2021

This article presents a multi-dimensional spatial pattern analysis of crime events in San Francisco. Our analysis includes the impact of spatial resolution on hotspot identification, temporal effects in crime spatial patterns, and relationships between various crime categories. In this work, crime prediction is viewed as a classification problem. When predictions for a particular category are made, a binary classification-based model is framed, and when all categories are considered for analysis, a multiclass model is formulated. The proposed crime-prediction model (HotBlock) utilizes spatiotemporal analysis for predicting crime in a fixed spatial region over a period of time. It is robust under variation of model parameters. HotBlock's results are compared with baseline real-world crime datasets. It is found that the proposed model outperforms the standard DeepCrime model in most cases.