• Journal of Convergence for Information Technology
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• v.8 no.6
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• pp.59-66
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• 2018

The utilized coefficient of friction (UCOF) as a ratio of the shear force to the normal force on the ground during walking is used to identify the point at which slip is likely to occur. Shoe walking will change the utilized coefficient of friction by shoe design such as sole thickness and hardness, heel shape, and outsole pattern. In this study, subjects are 21 adults (10 female, 11 male, age: $25.2{\pm}2.3yrs$, height: $165.6{\pm}7.2cm$), analysis variables were walking speed, GRF, when the UCOF is maximal, and Tangent of CoP-CoM angle, and correlation analysis with the utilized friction coefficient (UCOF). As a result, First, for the shod walking the time point which UCOF is maximum about heel strike was faster and the magnitude was larger than for barefoot walking. Second, the correlation between the tangent of CoP-CoM and UCOF of right foot was higher at the left heel striking point (UCOF2_h) which occurred in the post propulsion phase than at the right heel striking point (UCOF1_h). This suggests that the right foot UCOF is related to the braking phase of left foot( which is the propulsion phase of right foot) rather than the braking phase of right foot.

• Journal of Korea Foundry Society
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• v.39 no.2
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• pp.26-31
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• 2019

In this study, the mechanical characteristics and microstructure of hypereutectic Al-17Si-5Fe extruded alloys prepared by a rapid solidification process (RSP) were investigated. The hypereutectic Al alloy was fabricated by means of RSP and permanent casting. For RSP, the Al alloy melted at $920^{\circ}C$, cooling the specimens at a rate of $10^6^{\circ}C/s$ when the RSP was used, thus allowing the refining of primary Si particles more than when using permanent casting, at a rate of about 91%. We tested an extrusion RSP billet and a permanent-cast billet. Before the hot-extrusion process, heating to $450^{\circ}C$ took place for one hour. The samples were then hotextruded with a condition of extrusion ratio of 27 and a ram speed of 0.5 mm/s. Microstructural analyses of the extruded RSP method and the permanent casting method were carried out with OM and SEM-EDS mapping. The mechanical properties in both cases were evaluated by Vickers micro-hardness, wear resistance and tensile tests. It was found that when hypereutectic Al-17Si-5Fe alloys were fabricated by a rapid solidification method, it becomes possible to refine Si and intermetallic compounds. During the preparation of the hypereutectic Al-17Si-5Fe alloy by the rapid solidification method, the pressure of the melting crucible was low, and at faster drum speeds, smaller grain alloy flakes could be produced. Hot extrusion of the hypereutectic Al-17Si-5Fe alloy during the rapid solidification method required higher pressure levels than hot extrusion of the permanent mold-casted alloy. However, it was possible to produce an extruded material with a better surface than that of the hot extruded material processed by permanent mold casting.

• Food Engineering Progress
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• v.23 no.4
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• pp.283-289
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• 2019

This study was performed to determine the effect of psyllium husk addition on the physical properties of rice extrudates. Rice-based formulations mixed with psyllium husk (0, 7, 14 and 21%) were extruded at a die temperature of 140℃, screw speed of 200 rpm, and moisture content of 20%. As the content of psyllium husk increased, expansion ratio decreased, while piece density and specific length increased. Apparent elastic modulus, breaking strength, adhesiveness, and hardness augmented with an elevation in psyllium husk content. Lightness declined as psyllium husk content furthered, while redness, yellowness, and color difference intensified. Water soluble index and water absorption index increased with an increased amount of psyllium husk. In conclusion, the addition of psyllium affected the expansion of extruded rice snack possessing hard texture, small cells, and sticky texture due to higher water absorption during hydration.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.157-165
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• 2020

Aiming at the development of neural network and self-driving data set, it is also an idea to improve the performance of network model to detect moving objects by dividing the data set. In Darknet network framework, the YOLOv4 (You Only Look Once v4) network model was used to train and test Udacity data set. According to 7 proportions of the Udacity data set, it was divided into three subsets including training set, validation set and test set. K-means++ algorithm was used to conduct dimensional clustering of object boxes in 7 groups. By adjusting the super parameters of YOLOv4 network for training, Optimal model parameters for 7 groups were obtained respectively. These model parameters were used to detect and compare 7 test sets respectively. The experimental results showed that YOLOv4 can effectively detect the large, medium and small moving objects represented by Truck, Car and Pedestrian in the Udacity data set. When the ratio of training set, validation set and test set is 7:1.5:1.5, the optimal model parameters of the YOLOv4 have highest detection performance. The values show mAP50 reaching 80.89%, mAP75 reaching 47.08%, and the detection speed reaching 10.56 FPS.

• Korean Journal of Remote Sensing
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• v.36 no.6_3
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• pp.1711-1720
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• 2020

Particulate matter (PM) that has been artificially generated during the recent of rapid industrialization and urbanization moves and disperses according to weather conditions, and adversely affects the human skin and respiratory systems. The purpose of this study is to predict the PM10 concentration in Seoul using meteorological factors as input dataset for multiple linear regression (MLR), support vector machine (SVM), and random forest (RF) models, and compared and evaluated the performance of the models. First, the PM10 concentration data obtained at 39 air quality monitoring sites (AQMS) in Seoul were divided into training and validation dataset (8:2 ratio). The nine meteorological factors (mean, maximum, and minimum temperature, precipitation, average and maximum wind speed, wind direction, yellow dust, and relative humidity), obtained by the automatic weather system (AWS), were composed to input dataset of models. The coefficients of determination (R2) between the observed PM10 concentration and that predicted by the MLR, SVM, and RF models was 0.260, 0.772, and 0.793, respectively, and the RF model best predicted the PM10 concentration. Among the AQMS used for model validation, Gwanak-gu and Gangnam-daero AQMS are relatively close to AWS, and the SVM and RF models were highly accurate according to the model validations. The Jongno-gu AQMS is relatively far from the AWS, but since PM10 concentration for the two adjacent AQMS were used for model training, both models presented high accuracy. By contrast, Yongsan-gu AQMS was relatively far from AQMS and AWS, both models performed poorly.

• Economic and Environmental Geology
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• v.55 no.3
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• pp.309-316
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• 2022

In order to minimize the human and time consumption required for rock classification, research on rock classification using artificial intelligence (AI) has recently developed. In this study, basic volcanic rocks were subdivided by using polarizing microscope thin section images. A convolutional neural network (CNN) model based on Tensorflow and Keras libraries was self-producted for rock classification. A total of 720 images of olivine basalt, basaltic andesite, olivine tholeiite, trachytic olivine basalt reference specimens were mounted with open nicol, cross nicol, and adding gypsum plates, and trained at the training : test = 7 : 3 ratio. As a result of machine learning, the classification accuracy was over 80-90%. When we confirmed the classification accuracy of each AI model, it is expected that the rock classification method of this model will not be much different from the rock classification process of a geologist. Furthermore, if not only this model but also models that subdivide more diverse rock types are produced and integrated, the AI model that satisfies both the speed of data classification and the accessibility of non-experts can be developed, thereby providing a new framework for basic petrology research.

• Journal of Software Assessment and Valuation
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• v.16 no.1
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• pp.55-63
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• 2020

Lasers for optical broadband communication systems should have excellent frequency selectivity and modal stability. DFB lasers have low lasing frequency shift during high speed current modulation. In this paper, when a refractive index grating and a gain grating are simultaneously present in a DFB laser having a wavelength of 1.55 ㎛, the dielectric film is coated so that reflection does not occur on the right mirror surface, so that ρ_r=0. For the first mode, which requires a minimum gain at the threshold, the beam distribution of the oscillation mode in the longitudinal direction and the radiated power ratio P_l/P_r were analyzed and compared for the cases of the phase of ρ_l=π and π/2. If the phase of ρ_l=π, in order to obtain a low threshold current and high frequency stability, κL should be greater than 8. In the case of the phase of ρ_l=π/2, for low threshold current, κL is necessary to be 1.0, where the oscillation frequency coincides with the lattice frequency. DFB lasers with an anti-reflection coated mirror have excellent mode selectivity than 1.55um DFB lasers with two mirror facets

• Resources Recycling
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• v.31 no.2
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• pp.63-69
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• 2022

In this study, mechanical grinding using a planetary ball mill was performed under various conditions to evaluate its effect on the crystal structure of vanadium titanium magnetite (VTM) ore from the Kwain Mine in South Korea. The crystal structure of the activated product was also evaluated. Magnetite and ilmenite were identified as the main types of VTM ore used in the Kwain Mine, and the main types of gangue minerals were iron-based silicate minerals. According to the mechanical activation results, the crystallinity and crystal size decreased as the size of the grinding media (balls) decreased, and the amorphization of the sample/ball filling was significant as the amount of the sample was reduced. In addition, as the grinding speed and time increased, the crystal structure significantly changed, proving that these two parameters had a greater effect on the crystal structure than the ball size and sample/ball filling ratio.

• Journal of the Korean Geotechnical Society
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• v.24 no.6
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• pp.57-67
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• 2008

Two test methods, nonrepetitive plate loading test (NPLT) and repetitive plate loading test (RPLT) are being used to control the quality of compaction through the evaluation of the stiffness of subgrade soils in the Korea railway industry. Subgrade reaction modulus ($k_{30}$) from the NPLT and strain modulus ($E_v$) from the RPLT are the index values to check them. The methods have similar aspects, but they differ in the modulus evaluation method, the numbers of loading stage, termination procedures, etc. This paper analyses the differences of the two test methods and evaluates the relationship between subgrade reaction modulus and strain modulus. In order to develop the relationship, total 22 tests were performed including the NPLT and the RPLT at the 6 original grounds, and 5 upper or lower subgrades in Kyungbu High Speed Railway II stage construction sites. According to the soil conditions, the relationship between subgrade reaction modulus and strain modulus was proposed with corrections by considering strain states, mean confining pressures, and Poisson's ratio.

• 한국체육학회지인문사회과학편
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• v.57 no.6
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• pp.263-272
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• 2018

This study examined the association of gait variability and physical fitness with frailty status in older women. In a cross-sectional design, 168 elderly women, aged 65 years and older (75.07±5.40 years), measured body composition, gait parameters gait variability, physical fitness variables, MMSE-DS and CES-D. Subjects were classified as robust, pre-frail, and frailty based on the Fried et al.(2001) criteria for frailty weight loss, exhaustion, low hand-grip strength, low gait speed, and physical inactivity. Logistic regression analyses were used to determine the odds ratio (ORs) and 95% confidence interval (CI) of frailty status for having gait variability and physical fitness levels. Compared to the robust group (OR=1), the frailty group had significantly higher ORs of having terminal double limb stance (OR=1.48, 95% CI=0.10-2.21, p=.049), step cadence (OR=2.06, 95%CI=1.20-3.43, p=.009) variability, and significantly lower ORs of having upper-strength (OR=0.49, 95%CI=0.31-0.77, p=.002) even after adjusting for age, education, comorbidity, K-IADL, MMSE-KC and CES-D score. The finding of this study suggested that terminal double limb stance, step cadence and upper body muscular strength were independent predictors of frailty.