• Journal of the Korea Computer Industry Society
• /
• v.3 no.3
• /
• pp.259-270
• /
• 2002

In computer Go, the method evaluating the situation of a face is not generalized. To evaluate the situations all the faces accurately, computer Go must judge owners of 361 positions according the changes of the faces. In this paper, we apply the structure of graph as a method analyzing the rules and characters of Go. The Situation Evaluation System(SES) which can evaluate the situation of a face without DB information oかy using strength of stone(SS), influence power(IP), safety(S), position value(PV), and position-value matrix(PM) is proposed. This system is very effective to evaluate the whole situations of Go because it can show the owner of 361 positions between Black and White. As a result, SES can well compute the situations in the opening game of Go. It makes 70.9% hit-ratio as compared with the practical Go games of professional players. According to the results compared with Nemesis, the commercial program which has the joseki(established stones: hewn sequences of moves near the corner which result in near-equal positions for White and Black), SES is superior to Nemesis by 10% higher in the hit-ratio of situation evaluations of professional players.

• Journal of Physiology & Pathology in Korean Medicine
• /
• v.33 no.2
• /
• pp.116-122
• /
• 2019

The aim of this study is to evaluate the anti-inflammatory effect of Hataedock treatment using Coptidis Rhizome and Glycyrrhiza Uralensis (CG) mixed extract in allergic rhinitis induced NC/Nga mice. We divided NC/Nga mice into 3 groups as follows; allergic rhinitis-induced group after CG Hataedock treatment (CGT, n=10), no treatment group (Ctrl), allergic rhinitis elicited group (ARE). To induce allergic rhinitis, NC/Nga mice of 3 weeks age were sensitized on 7, 8 and 9week by Ovalbumin (OVA) antigen in intranasal space. Hataedock using CG extract was administered on week 3 in allergic rhinitis-induced group (CGT) after Hataedock treatment. To identify distribution of Interlukin (IL)-4, Cluster of differentiation 40 (CD40), high-affinity IgE receptor ($Fc{\varepsilon}RI$), substance P, Matrix metallopeptidase 9 (MMP-9), Nuclear $factor-{\kappa}B$ ($NF-{\kappa}B$) p65, Inducible nitric oxide synthase (iNOS) and Cycloxygenase-2 (COX-2), we used histological examination. CGT significantly inhibited IL-4 and CD40 response compared with ARE. The reduction of Th2 cytokine expression decreased inflammatory mediators such as $Fc{\varepsilon}RI$, substance P, MMP-9, $NF-{\kappa}B$ p65, iNOS and COX-2. Such immunological improvement induced reduction of respiratory epithelial damage and mucin secretion in goblet cell. These results indicate that Hataedock treatment suppresses allergic rhinitis through modulating of Th2 responses and diminishing various inflammatory mediators in nasal mucosal tissue. It might have potential applications for prevention and treatment of allergic rhinitis.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.8
• /
• pp.3917-3941
• /
• 2019

The recent interest in artificial intelligence and machine learning has partly contributed to an interest in the use of such approaches for hyperspectral remote sensing (HRS) imagery classification, as evidenced by the increasing number of deep framework with deep convolutional neural networks (CNN) structures proposed in the literature. In these approaches, the assumption of obtaining high quality deep features by using CNN is not always easy and efficient because of the complex data distribution and the limited sample size. In this paper, conventional handcrafted learning-based multi features based on expert knowledge are introduced as the input of a special designed CNN to improve the pixel description and classification performance of HRS imagery. The introduction of these handcrafted features can reduce the complexity of the original HRS data and reduce the sample requirements by eliminating redundant information and improving the starting point of deep feature training. It also provides some concise and effective features that are not readily available from direct training with CNN. Evaluations using three public HRS datasets demonstrate the utility of our proposed method in HRS classification.

• Biomedical Science Letters
• /
• v.25 no.1
• /
• pp.40-53
• /
• 2019

Of the Acinetobacter spp., A. baumannii (genospecies 2) is the most clinically significant in terms of hospital-acquired infections worldwide. It is difficult to perform Acinetobacter-related taxonomy using phenotypic characteristics and routine laboratory methods owing to clusters of closely related species. The ability to accurately identify Acinetobacter spp. is clinically important because antimicrobial susceptibility and clinical relevance differs significantly among the different genospecies. Based on the medical importance of pathogenic Acinetobacter spp., the distribution and characterization of Acinetobacter spp. isolates from 123 clinical samples was determined in the current study using four typically applied bacterial identification methods; partial rpoB gene sequencing, amplified rRNA gene restriction analysis (ARDRA) of the intergenic transcribed spacer (ITS) region of the 16~23S rRNA, the $VITEK^{(R)}$ 2 system (an automated microbial identification system) and matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS). A. baumannii isolates (74.8%, 92/123) were the most common species, A. nosocomialis (10.6%, 13/123) and A. pittii isolates (7.5%, 9/123) were second and third most common strains of the A. calcoaceticus-A. baumannii (ACB) complex, respectively. A. soli (5.0%, 6/123) was the most common species of the non-ACB complex. RpoB gene sequencing and ARDRA of the ITS region were demonstrated to lead to more accurate species identification than the other methods of analysis used in this study. These results suggest that the use of rpoB genotyping and ARDRA of the ITS region is useful for the species-level identification of Acinetobacter isolates.

• Composites Research
• /
• v.32 no.3
• /
• pp.163-169
• /
• 2019

In this paper, we constructed a molecular dynamics (MD) polymer model of PMMA with 95% of conversion by using dynamic polymerization algorithm of a thermoplastic polymer based on free radical polymerization. In this algorithm, we introduced a united-atom level coarse-grained force field that combines the non-bonded terms from the TraPPE-UA force field and the bonded terms from the PCFF force field to alleviate the computation efforts. The molecular weight distribution and the average molecular weight of the polymer were calculated by investigating each chain generated from the free radical polymerization simulation. The molecular weight of the polymer was controlled by the number of initiator radicals presented in the initial state and molecular weight effect to the density, the glass transition temperature, and the mechanical properties were studied.

• Structural Engineering and Mechanics
• /
• v.71 no.4
• /
• pp.391-405
• /
• 2019

Compared to the ambient vibration test mainly identifying the structural modal parameters, such as frequency, damping and mode shapes, the impact testing, which benefits from measuring both impacting forces and structural responses, has the merit to identify not only the structural modal parameters but also more detailed structural parameters, in particular flexibility. However, in traditional impact tests, an impacting hammer or artificial excitation device is employed, which restricts the efficiency of tests on various bridge structures. To resolve this problem, we propose a new method whereby a moving vehicle is taken as a continuous exciter and develop a corresponding flexibility identification theory, in which the continuous wheel forces induced by the moving vehicle is considered as structural input and the acceleration response of the bridge as the output, thus a structural flexibility matrix can be identified and then structural deflections of the bridge under arbitrary static loads can be predicted. The proposed method is more convenient, time-saving and cost-effective compared with traditional impact tests. However, because the proposed test produces a spatially continuous force while classical impact forces are spatially discrete, a new flexibility identification theory is required, and a novel structural identification method involving with equivalent load distribution, the enhanced Frequency Response Function (eFRFs) construction and modal scaling factor identification is proposed to make use of the continuous excitation force to identify the basic modal parameters as well as the structural flexibility. Laboratory and numerical examples are given, which validate the effectiveness of the proposed method. Furthermore, parametric analysis including road roughness, vehicle speed, vehicle weight, vehicle's stiffness and damping are conducted and the results obtained demonstrate that the developed method has strong robustness except that the relative error increases with the increase of measurement noise.

• The Journal of Internal Korean Medicine
• /
• v.40 no.1
• /
• pp.1-12
• /
• 2019

Objective: To investigate the effect of Alpiniae oxyphyllae fructus (AOF) on the alleviation of musculoskeletal disorders caused by aging, we conducted experiments on osteoporosis and muscle atrophy. Methods: The experimental group was classified into a control group, aging-elicited (AE) group and AOF group. The control group comprised 8-week-old Institute of Cancer Research (ICR) mice. The AE and AOF groups were ICR mice at 50 weeks of age. For the AE group, 10 mL of distilled water was administered once a day for 180 days without any treatment. An AOF extract (0.54 g/kg) was dissolved in distilled water and administered to the mice in the AOF group once a day for 180 days. Results: In the experiment on the alleviation of osteoporosis, the distribution of glucosaminoglycan in the bone matrix of the femoral bone was increased in the AOF group; moreover, the osteocalcin (OCN) positive reaction was increased and 8-OHdG positivity was decreased. In addition, AOF positively decreased RANKL, positively increased OPG, and positively decreased MMP-3. Muscle fiber loss in the endomysium following muscle degeneration of the quadriceps was reduced more in the AOF group compared with the AE group, and caspase-3 positive responses were also decreased. In addition, the 8-OHdG and p-lkB positivity in the AOF group decreased compared with the AE group, and the Myo-D positivity increased. Conclusion: We found that increasing bone formation alleviates osteoporosis, and that reducing bone loss alleviates muscle atrophy by reducing muscle loss and increasing muscle development.

• Applied Chemistry for Engineering
• /
• v.30 no.2
• /
• pp.233-240
• /
• 2019

Molecular recognition technology has attracted considerable attention for improving the selectivity of a specific molecule by imprinting it on a polymer matrix. In this study, adsorption and release characteristics of chitosan based drug delivery films imprinted with sulindac (SLD) were investigated in terms of the plasticizer, temperature and pH and the results were also interpreted by the related mathematical models. The adsorption characteristics of target molecules on SLD-imprinted polymer films were better explained by the Freundlich and Sips equation than that of the Langmuir equation. The binding site energy distribution function was also useful for understanding the adsorption relationship between target molecules and polymer films. The drug release of SLD-imprinted polymer films followed the Fickian diffusion mechanism, whereas the drug release using artificial skin followed the non-Fickian diffusion behavior.

• Transactions of Materials Processing
• /
• v.30 no.1
• /
• pp.5-15
• /
• 2021

The effects of heat treatments (T6 and T73) on the microstructure, mechanical properties, and high cycle fatigue behavior of modified AA7075 alloys were investigated. A modified 7075 alloy was manufactured using modified-Mg (Mg-Al2Ca) instead of the conventional element Mg. Based on the microstructure, the average grain size was 4.5 ㎛ (T6) and 5.2 ㎛ (T73). Regardless of heat treatment, the modified AA7075 alloys consisted of Al matrix containing homogeneously distributed Al2CuMg and MgZn2 phases with reduced Fe-intermetallic compound. Room temperature tensile tests showed that the properties of modified 7075-T6 (Y.S.: 622MPa, T.S: 675MPa, elongation: 15.4%) were superior to those of T73 alloy (Y.S.: 492MPa, T.S: 548MPa, elongation: 12.8%). Experimental data show that the fatigue life of T6 was 400 MPa, about 64% of its yield strength. However, the fatigue life of T73 alloy was 330 MPa and 67%. Irrespective of the stress level, all crack initiation points were located on the specimen surface, and no inclusions acting as stress concentrators were seen. Superior mechanical properties and high cycle fatigue behavior of modified AA7075-T6 alloy are attributed to the fine grains and homogeneous distribution of small second phases such as MgZn2 and Al2CuMg, in addition to reduced Fe-intermetallic compounds.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.1
• /
• pp.56-62
• /
• 2021

High forecast accuracy is required as social issues on particulate matter increase. Therefore, many attempts are being made using machine learning to increase the accuracy of particulate matter prediction. However, due to problems with the distribution of imbalance in the concentration and various characteristics of particulate matter, the learning of prediction models is not well done. In this paper, to solve these problems, a binary classification model was proposed to predict the concentration of particulate matter needed for prediction by dividing it into two classes based on the value of 80㎍/㎥. Four classification algorithms were utilized for the binary classification of PM10. Classification algorithms used logistic regression, decision tree, SVM, and MLP. As a result of performance evaluation through confusion matrix, the MLP model showed the highest binary classification performance with 89.98% accuracy among the four models.