• KIEAE Journal
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• v.11 no.5
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• pp.13-18
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• 2011

The overall aim of this study is to mitigate urban environmental problems. In particular, to reduce the effects of urban heat island phenomenon which is one of the urban planning perspective. This study focused on the analysis of the relationship between the urban heat island effect and the thermal and wind properties. To do this analysis, water space was virtually made at Yeol_Mae village Apt. Because it is very difficult to set up water space for the existing apartment complexes due to realistic constraints. This study, therefore has a strong sort of guidelines to create water space for newly formed city. It was based on the concept of virtual city through an in-depth analysis on reduction of urban heat island effects for the existing apartment along with creation of water space. To analysis site, Envi-Met Model developed by Michael Bruse was used. The results are as follows. The temperature went from 298.9K to 297.82K and The wind speed went from 1.42m/s to 1.43m/s. The results are slight in this study because creation of water space is planned to a small area of an apartment complex. But if the water space would be applied to a whole city, the mitigation effect of urban heat island would be bigger.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.6
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• pp.2480-2496
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• 2020

Considering that high-dose X-ray radiation during CT scans may bring potential risks to patients, in the medical imaging industry there has been increasing emphasis on low-dose CT. Due to complex statistical characteristics of noise found in low-dose CT images, many traditional methods are difficult to preserve structural details effectively while suppressing noise and artifacts. Inspired by the deep learning techniques, we propose a densely connected residual network (DCRN) for low-dose CT image noise cancelation, which combines the ideas of dense connection with residual learning. On one hand, dense connection maximizes information flow between layers in the network, which is beneficial to maintain structural details when denoising images. On the other hand, residual learning paired with batch normalization would allow for decreased training speed and better noise reduction performance in images. The experiments are performed on the 100 CT images selected from a public medical dataset-TCIA(The Cancer Imaging Archive). Compared with the other three competitive denoising algorithms, both subjective visual effect and objective evaluation indexes which include PSNR, RMSE, MAE and SSIM show that the proposed network can improve LDCT images quality more effectively while maintaining a low computational cost. In the objective evaluation indexes, the highest PSNR 33.67, RMSE 5.659, MAE 1.965 and SSIM 0.9434 are achieved by the proposed method. Especially for RMSE, compare with the best performing algorithm in the comparison algorithms, the proposed network increases it by 7 percentage points.

• Journal of the Korea Society of Computer and Information
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• v.28 no.11
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• pp.13-20
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• 2023

In this paper, we propose a water temperature prediction method using feature extraction and reconstructed data based on LSTM-Autoencoder. We used multivariate time series data such as sea surface water temperature in the Naksan area of the East Sea where the cold water zone phenomenon occurred, and wind direction and wind speed that affect water temperature. Using the LSTM-Autoencoder model, we used three types of data: feature data extracted through dimensionality reduction of the original data combined with multivariate data of the original data, reconstructed data, and original data. The three types of data were trained by the LSTM model to predict sea surface water temperature and evaluated the accuracy. As a result, the sea surface water temperature prediction accuracy using feature extraction of LSTM-Autoencoder confirmed the best performance with MAE 0.3652, RMSE 0.5604, MAPE 3.309%. The result of this study are expected to be able to prevent damage from natural disasters by improving the prediction accuracy of sea surface temperature changes rapidly such as the cold water zone.

• Genomics & Informatics
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• v.21 no.4
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• pp.46.1-46.10
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• 2023

Colon adenocarcinoma (COAD) is the predominant type of colorectal cancer. Early diagnosis and treatment can significantly improve the prognosis of COAD patients. Anoctamin 7 (ANO7), an anion channel protein, has been implicated in prostate cancer and other types of cancer. In this study, we analyzed the expression of ANO7 and its correlation with clinicopathological characteristics among COAD patients using the Gene Expression Profiling Interactive Analysis 2 (GEPIA2) and the University of Alabama at Birmingham CANcer (UALCAN) databases. The GEPIA2, Kaplan-Meier plotter, and the Survival Genie platform were employed for survival analysis. The co-expression network and potential function of ANO7 in COAD were analyzed using GeneFriends, the Database for Annotation, Visualization and Integrated Discovery (DAVID), GeneMANIA, and Pathway Studio. Our data analysis revealed a significant reduction in ANO7 expression levels within COAD tissues compared to normal tissues. Additionally, ANO7 expression was found to be associated with race and histological subtype. The COAD patients exhibiting low ANO7 expression had lower survival rates compared to those with high ANO7 expression. The genes correlated with ANO7 were significantly enriched in proteolysis and mucin type O-glycan biosynthesis pathway. Furthermore, ANO7 demonstrated a direct interaction and a positive co-expression correlation with mucin 2 (MUC2). In conclusion, our findings suggest that ANO7 might serve as a potential prognostic biomarker and potentially plays a role in proteolysis and mucin biosynthesis in the context of COAD.

• Journal of Electrical Engineering and Technology
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• v.10 no.5
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• pp.2197-2204
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• 2015

In recent years, medical image diagnosis has growing significant momentous in the medicinal field. Brain and lung image of patient are distorted with salt and pepper noise is caused by moving the head and chest during scanning process of patients. Reconstruction of these images is a most significant field of diagnostic evaluation and is produced clearly through techniques such as linear or non-linear filtering. However, restored images are produced with smaller amount of noise reduction in the presence of huge magnitude of salt and pepper noises. To eliminate the high density of salt and pepper noises from the reproduction of images, a new efficient fuzzy based median filtering algorithm with a moderate elapsed time is proposed in this paper. Reproduction image results show enhanced performance for the proposed algorithm over other available noise reduction filtering techniques in terms of peak signal -to -noise ratio (PSNR), mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE), image enhancement factor (IMF) and structural similarity (SSIM) value when tested on different medical images like magnetic resonance imaging (MRI) and computer tomography (CT) scan brain image and CT scan lung image. The introduced algorithm is switching filter that recognize the noise pixels and then corrects them by using median filter with fuzzy two-sided π- membership function for extracting the local information.

• Journal of Korean Medical Ki-Gong Academy
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• v.14 no.1
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• pp.83-98
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• 2014

Objects : This study is a report on treatment effect of the case that treated by using of Korean medical treatment to phyllodes tumors(PT) of breast patient. Methods : The patient diagnosed with PT of breast was treated by using of acupuncture, manipulation therapy and herbal medicine. VAS scale was used as the tool of treatment effect. Results : Although the tumor size was intact, the Korean medical treatment reduced the breast pain(VAS 5 → 1). Conclusions : This study suggests that the oriental medical treatment might be useful for breast pain reduction in PT of breast patient, and make a psychological stability of the patient.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2019.06a
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• pp.272-273
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• 2019

VVC(Versatile Video Coding)는 YUV 입력 영상에 대하여 Luma 성분과 Chroma 성분에 대하여 각각 다른 최적의 방법으로 블록분할 후 해당 블록에 대해서 화면 내 예측 또는 화면 간 예측을 수행하고, 예측영상과 원본영상의 차이를 변환, 양자화하여 압축한다. 이 과정에서 복원영상에는 블록화 노이즈, 링잉 노이즈, 블러링 노이즈 발생한다. 본 논문에서는 인코더에서 원본영상과 복원영상의 잔차신호에 대한 MAE(Mean Absolute Error)를 추가정보로 전송하여 이 추가정보와 복원영상을 이용하여 Deep Learning 기반의 신경망 네트워크로 영상의 품질을 높이는 방법을 제안한다. 복원영상의 노이즈를 감소시키기 위하여 영상을 $32{\times}32$블록의 임의로 분할하고, DenseNet기반의 UNet 구조로 네트워크를 구성하였다.

• Korean Journal of Acupuncture
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• v.28 no.2
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• pp.49-58
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• 2011

Objectives : The purpose of this study is examining the effects of appling acupressure to acupuncture points (study group) and Interferential current therapy (ICT) to cervical region (control group) on the cerebral blood flow of 20 tension-type headache patients and the reduction of their headaches. For approaching this examination, clinical research was conducted for three weeks those two groups, each contains 10 patients. Methods : We stimulated 7 acupuncture points for headache with the acupressure (for three weeks) and applied ICT to cervical region. Also we measured VAS (visual analogue scale) and the blood flow of the vertebral arteries with TCD (transcranial doppler ultrasonography). Results : (1) When the left and right vertebral artery of study group was compared each time, significant differences were found after the 1st treatment (p<.001). Also the significant differences were found after 2, 3weeks treatment (p<.05). (2) When the Visual Analog Scale of study group were compared periodically, the significant reductions were found after the 1 week treatments (p<.05). Also the significant differences were found after 2, 3 weeks treatments (p<.001). In the case of the control group, the significant reduction were found after the 2 and 3 weeks treatments (p<.001). Conclusions : The acupressure applied to acupuncture points reduced the headache and increased the ratio of cerebral blood flow.

• Journal of Microbiology and Biotechnology
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• v.19 no.6
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• pp.604-609
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• 2009

To investigate the potential use of microbial heme as an iron source, recombinant Escherichia coli coexpressing ALA synthase (HemA) as well as the NADP-dependent malic enzyme (MaeB) and dicarboxylic acid transporter (DctA) were cultured. The typical red pigment extracted from the recombinant E. coli after 38 h showed highest absorbance at 407 nm, and the amount of iron in 38.4 mg of microbial heme extract derived from 6-1 fermentation broth was 4.1 mg. To determine the commercial potential of the recombinant E.coli-synthesized iron-associated heme as an iron source, mice were fed the iron-free provender with the microbial heme extract. The average body weight reduction of mice fed non-iron provender was 2.3%, whereas no detectable weight loss was evident in mice fed microbial heme addition after 15 days. The heme content of the blood from microbial heme fed mice was 4.2 mg/ml whereas that of controls was 2.4 mg/ml, which implies that the microbial heme could be available for use as an animal iron source.

• Journal of Environmental Science International
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• v.27 no.7
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• pp.499-507
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• 2018

Agricultural meteorological information is an important resource that affects farmers' income, food security, and agricultural conditions. Thus, such data are used in various fields that are responsible for planning, enforcing, and evaluating agricultural policies. The meteorological information obtained from automatic weather observation systems operated by rural development agencies contains missing values owing to temporary mechanical or communication deficiencies. It is known that missing values lead to reduction in the reliability and validity of the model. In this study, the hierarchical Bayesian spatio-temporal model suggests replacements for missing values because the meteorological information includes spatio-temporal correlation. The prior distribution is very important in the Bayesian approach. However, we found a problem where the spatial decay parameter was not converged through the trace plot. A suitable spatial decay parameter, estimated on the bias of root-mean-square error (RMSE), which was determined to be the difference between the predicted and observed values. The latitude, longitude, and altitude were considered as covariates. The estimated spatial decay parameters were 0.041 and 0.039, for the spatio-temporal model with latitude and longitude and for latitude, longitude, and altitude, respectively. The posterior distributions were stable after the spatial decay parameter was fixed. root mean square error (RMSE), mean absolute error (MAE), mean absolute percentage error (MAPE), and bias were calculated for model validation. Finally, the missing values were generated using the independent Gaussian process model.