• Korean Journal of Fisheries and Aquatic Sciences
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• v.12 no.4
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• pp.201-207
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• 1979

The stow net now used in the Yellow Sea, are traditional bag net with the opening held by a lighter upper and a weighted lower beams standing against the current. Such bag net anchored at the bottom are known in many countries, particularly in the estuaries of large rivers, but more rarely in sea fisheries, because they are too much affected by the weather, moreover a permanent strong current is necessary. Some scientists intended to improve this fishing gear, using the shearing devices instead of a lighter upper and a weighted lower beams in order to widen mouth of the stow net however they are unsuccessful. One-fortieth scale model net of the stow net was tested in a circular water tank with an effective volume of $5.67m\times1.76m\times1.00m$ of observing the configuration and tension of the net. Experiments were carried out under the various combination including water velocity, spherical floats and elevating floats with the shearing hoods instead of the upper beam. We found those devices offered a very low resistance per net area to current compared with the spherical floats or upper beam, and had a fairly good shearing power at any velocity and direction of the current. The total resistance (R) of the model net to which shearing hoods and floats are attached can be induced by the following formula under the condition of 0.25m/sec to 0.5m/sec, $$R(kg)=3.11V^{1.54}$$ The height (h) of the improved model net (m-B) is higher than traditional model net(m-A) with upper and lower beams, m-A: h(cm)=89.22-2.42(V-15). $V\geqq15,\;cm/sec$ m-B: h(cm)=89.20-0.78V (V:cm/sec) The catch efficiency of improved model net is 1.5 times traditional model net.

• The Korean Journal of Nuclear Medicine
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• v.28 no.2
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• pp.172-176
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• 1994

As the Tc-99m-MIBI myocardial SPECT demonstrated wide application in the diagnosis of myocardial function, the quantitative and severity-dependent information is currently re quired. In this study, we proposed a computerized method for scoring the fixed defects in terms of extent-weighted severity and for identifying the reversibility in ischemic regions. At the first stage of this method, the transverse slices were reconstructed with 0.4 Nyquist freq. and order 5 Butterworth filter. From the oblique/sagittal slices, maximal count per pixel circumferential profiles were extracted for each sector, and then stress/redist. polar maps were normalized and plotted. For reversibility, the stress polar map was subtracted from the de-layed image and positive-valued pixels were categorized into three grades. The extent-weight-ed severity scores were calculated using the assigned grades and their number of pixels. This procedure was done automatically and the reversibility and severity scores were produced for each of the coronary territories (LAD, RCA, LCX) or any combination of these. Clinical ap-plication has shown that the changes In reversibility scores after PTCA were correlated linearly with the pre PTCA scores(r>0.8) in postinfarct cases as well as in angina, and severity scores of persistent defects in stress/rest SPECT study matched to the regional ejection fraction and visual analysis of regional wall motion of gated blood pool scan(r>0.6). We conclude that the computerized severity scoring method for the analysis of myocardial SPECT could be useful in the assessment of the myocardial ischemia and fixed defect.

• Genomics & Informatics
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• v.10 no.3
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• pp.175-183
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• 2012

Colorectal cancer (CRC) is among the leading causes of cancer deaths and can be caused by environmental factors as well as genetic factors. Therefore, we developed a prediction model of CRC using genetic risk scores (GRS) and evaluated the effects of conventional risk factors, including family history of CRC, in combination with GRS on the risk of CRC in Koreans. This study included 187 cases (men, 133; women, 54) and 976 controls (men, 554; women, 422). GRS were calculated with most significantly associated single-nucleotide polymorphism with CRC through a genomewide association study. The area under the curve (AUC) increased by 0.5% to 5.2% when either counted or weighted GRS was added to a prediction model consisting of age alone (AUC 0.687 for men, 0.598 for women) or age and family history of CRC (AUC 0.692 for men, 0.603 for women) for both men and women. Furthermore, the risk of CRC significantly increased for individuals with a family history of CRC in the highest quartile of GRS when compared to subjects without a family history of CRC in the lowest quartile of GRS (counted GRS odds ratio [OR], 47.9; 95% confidence interval [CI], 4.9 to 471.8 for men; OR, 22.3; 95% CI, 1.4 to 344.2 for women) (weighted GRS OR, 35.9; 95% CI, 5.9 to 218.2 for men; OR, 18.1, 95% CI, 3.7 to 88.1 for women). Our findings suggest that in Koreans, especially in Korean men, GRS improve the prediction of CRC when considered in conjunction with age and family history of CRC.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.12
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• pp.471-480
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• 2016

Recently, the damage of cyber attack toward infra-system, national defence and security system is gradually increasing. In this situation, military recognizes the importance of cyber warfare, and they establish a cyber system in preparation, regardless of the existence of threaten. Thus, the study of Intrusion Detection System(IDS) that plays an important role in network defence system is required. IDS is divided into misuse and anomaly detection methods. Recent studies attempt to combine those two methods to maximize advantagesand to minimize disadvantages both of misuse and anomaly. The combination is called Hybrid IDS. Previous studies would not be inappropriate for near real-time network environments because they have computational complexity problems. It leads to the need of the study considering the structure of IDS that have high detection rate and low computational cost. In this paper, we proposed a Hybrid IDS which combines C4.5 decision tree(misuse detection method) and Weighted K-means algorithm (anomaly detection method) hierarchically. It can detect malicious network packets effectively with low complexity by applying mutual information and genetic algorithm based efficient feature selection technique. Also we construct upgraded the the hierarchical structure of IDS reusing feature weights in anomaly detection section. It is validated that proposed Hybrid IDS ensures high detection accuracy (98.68%) and performance at experiment section.

• Korean Journal of Clinical Laboratory Science
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• v.51 no.2
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• pp.171-176
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• 2019

A comparative study between commercially available mycobacteria growth indicator tubes (MGIT) in the BACTEC MGIT 960 System and the conventional Ogawa media was carried out to assess the effectiveness of the re-decontaminating process for the recovery of mycobacteria. Processed specimens with 5% sodium hydroxide and 0.5% N-acetyl-L-cysteine were inoculated into MGIT and Ogawa media. The acid fast bacilli (AFB) recovered from the cultures were identified using a mycobacterium tuberculosis (TB) antigen kit. If contaminants were observed in the MGIT tubes within five days, a decontaminating process was repeated. A total of 1,190 out of 4,790 (24.8%) specimens showed positive results using the BACTEC MGIT 960 system. Among them, 278 specimens were reprocessed. When the MGIT and Ogawa results were compared, it showed discordant results (weighted kappa value: 0.283). One TB and 10 nontuberculous mycobacteria (NTM) were newly detected in MGIT only. The likely benefit of the re-decontaminating process is the detection of additional mycobacteria that could not be detected without a re-decontaminating process despite being small in number. In addition to the combination of MGIT and Ogawa, the re-decontaminating process is recommended in the case of contaminations to recover mycobacteria.

• Korean Journal of Radiology
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• v.22 no.9
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• pp.1514-1524
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• 2021

Objective: To develop a radiomics risk score based on dynamic contrast-enhanced (DCE) MRI for prognosis prediction in patients with glioblastoma. Materials and Methods: One hundred and fifty patients (92 male [61.3%]; mean age ± standard deviation, 60.5 ± 13.5 years) with glioblastoma who underwent preoperative MRI were enrolled in the study. Six hundred and forty-two radiomic features were extracted from volume transfer constant (K^trans), fractional volume of vascular plasma space (V_p), and fractional volume of extravascular extracellular space (V_e) maps of DCE MRI, wherein the regions of interest were based on both T1-weighted contrast-enhancing areas and non-enhancing T2 hyperintense areas. Using feature selection algorithms, salient radiomic features were selected from the 642 features. Next, a radiomics risk score was developed using a weighted combination of the selected features in the discovery set (n = 105); the risk score was validated in the validation set (n = 45) by investigating the difference in prognosis between the "radiomics risk score" groups. Finally, multivariable Cox regression analysis for progression-free survival was performed using the radiomics risk score and clinical variables as covariates. Results: 16 radiomic features obtained from non-enhancing T2 hyperintense areas were selected among the 642 features identified. The radiomics risk score was used to stratify high- and low-risk groups in both the discovery and validation sets (both p < 0.001 by the log-rank test). The radiomics risk score and presence of isocitrate dehydrogenase (IDH) mutation showed independent associations with progression-free survival in opposite directions (hazard ratio, 3.56; p = 0.004 and hazard ratio, 0.34; p = 0.022, respectively). Conclusion: We developed and validated the "radiomics risk score" from the features of DCE MRI based on non-enhancing T2 hyperintense areas for risk stratification of patients with glioblastoma. It was associated with progression-free survival independently of IDH mutation status.

• Journal of Internet Computing and Services
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• v.16 no.1
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• pp.67-74
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• 2015

In recent years, frequent itemset mining for considering the importance of each item has been intensively studied as one of important issues in the data mining field. According to strategies utilizing the item importance, itemset mining approaches for discovering itemsets based on the item importance are classified as follows: weighted frequent itemset mining, frequent itemset mining using transactional weights, and utility itemset mining. In this paper, we perform empirical analysis with respect to frequent itemset mining algorithms based on transactional weights. The mining algorithms compute transactional weights by utilizing the weight for each item in large databases. In addition, these algorithms discover weighted frequent itemsets on the basis of the item frequency and weight of each transaction. Consequently, we can see the importance of a certain transaction through the database analysis because the weight for the transaction has higher value if it contains many items with high values. We not only analyze the advantages and disadvantages but also compare the performance of the most famous algorithms in the frequent itemset mining field based on the transactional weights. As a representative of the frequent itemset mining using transactional weights, WIS introduces the concept and strategies of transactional weights. In addition, there are various other state-of-the-art algorithms, WIT-FWIs, WIT-FWIs-MODIFY, and WIT-FWIs-DIFF, for extracting itemsets with the weight information. To efficiently conduct processes for mining weighted frequent itemsets, three algorithms use the special Lattice-like data structure, called WIT-tree. The algorithms do not need to an additional database scanning operation after the construction of WIT-tree is finished since each node of WIT-tree has item information such as item and transaction IDs. In particular, the traditional algorithms conduct a number of database scanning operations to mine weighted itemsets, whereas the algorithms based on WIT-tree solve the overhead problem that can occur in the mining processes by reading databases only one time. Additionally, the algorithms use the technique for generating each new itemset of length N+1 on the basis of two different itemsets of length N. To discover new weighted itemsets, WIT-FWIs performs the itemset combination processes by using the information of transactions that contain all the itemsets. WIT-FWIs-MODIFY has a unique feature decreasing operations for calculating the frequency of the new itemset. WIT-FWIs-DIFF utilizes a technique using the difference of two itemsets. To compare and analyze the performance of the algorithms in various environments, we use real datasets of two types (i.e., dense and sparse) in terms of the runtime and maximum memory usage. Moreover, a scalability test is conducted to evaluate the stability for each algorithm when the size of a database is changed. As a result, WIT-FWIs and WIT-FWIs-MODIFY show the best performance in the dense dataset, and in sparse dataset, WIT-FWI-DIFF has mining efficiency better than the other algorithms. Compared to the algorithms using WIT-tree, WIS based on the Apriori technique has the worst efficiency because it requires a large number of computations more than the others on average.

• Particle and aerosol research
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• v.17 no.4
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• pp.91-106
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• 2021

Daily PM_2.5 was collected during summer period in 2020 in Gwangju to investigate its chemical and light absorption properties. In addition, real-time light absorption coefficients were observed using a dual-spot 7-wavelength aethalometer. During the study period, SO₄^2- was the most important contributor to PM_2.5, accounting for on average 33% (10-64%) of PM_2.5. The chemical form of SO₄^2- was appeared to be combination of 70% (NH₄)₂SO₄ and 30% NH₄HSO₄. Concentration-weighted trajectory (CWT) analysis indicated that SO₄^2- particles were dominated by local pollution, rather than regional transport from China. A combination of aethalometer-based and water-extracted brown carbon (BrC) absorption indicated that light absorption of BrC due to aerosol particles was 1.6 times higher than that due to water-soluble BrC, but the opposite result was found in absorption Ångström exponent (AAE) values. Lower AAE value by aerosol BrC particles was due to the light absorption of aerosol BrC by both water-soluble and insoluble organic aerosols. The BrC light absorption was also influenced by both primary sources (e.g., traffic and biomass burning emissions) and secondary organic aerosol formation. Finally the ATR-FTIR analysis confirmed the presence of NH₄⁺, C-H groups, SO₄^2-, and HSO₄^2-. The presence of HSO₄^2- supports the result of the estimated composition ratio of inorganic sulfate ((NH₄)₂SO₄) and bisulfate (NH₄HSO₄).

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.11
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• pp.144-151
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• 1998

In this paper, it is applied the analysis properties of mathematical morphology in order to process MIN/MAX operation on the basis of combination of predefined and weighted structuring element to FCNN having the structure of CNN combined with fuzzy logic between template and input/output. In this paper, as the fuzzy estimator is applied to the image including noise, thus it could be found the noise removal as well as the edge detection in the process of computer simulation. We could analyze and compare the results of edge detection using FCNN, CNN and median filter to which the erosion operation of morphology is applied. This paper could apply the static template and the variable template to FCNN using the quantization fuzzy function, in result we could confirm that the performance of FCNN got to improve in the process of computer simulation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.9
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• pp.1816-1821
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• 2016

Protein secondary structure is important for the study of protein evolution, structure and function of proteins which play crucial roles in most of biological processes. This paper try to effectively extract protein secondary structure information from the large protein structure database in order to predict the protein secondary structure of a query protein sequence. To find more remote homologous sequences of a query sequence in the protein database, we used PSI-BLAST which can perform gapped iterative searches and use profiles consisting of homologous protein sequences of a query protein. The secondary structures of the homologous sequences are weighed combined to the secondary structure prediction according to their relative degree of similarity to the query sequence. When homologous sequences with a neural network predictor were used, the accuracies were higher than those of current state-of-art techniques, achieving a Q3 accuracy of 92.28% and a Q8 accuracy of 88.79%.