• Journal of the Korea Convergence Society
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• v.11 no.2
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• pp.271-279
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• 2020

Squats and lunges are important exercises for strengthening the trunk and lower body among various free weight exercises. It should be achieved safe and effective excise through establishing of theoretical basis for exercise posture and standard movement. Therefore, it's necessary to develop the exercise model in order to prepare the scientific countermeasures for the prevent injuries and error movement through optimal exercise movement. For this purpose, it is effective to use appropriate instruments for motion compensation according to the optical motion and error motion. In this paper, we develop a motion model analysis system based on dynamic motion through the four-point load cell for dynamic motion analysis. Proposed analytical method, the optimal and the error motion numerical data is obtained through the dynamic motion analysis. And we verified that dynamic movement is simplified to establish the motion modeling according to the classification motion and the numerical quantification data for analyzing.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.5
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• pp.209-214
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• 2018

In this paper, we recognize the damage caused by a disaster to a facility in the event of a large-scale disaster and present the possible disasters in the form of a matrix. The typhoon was selected as a major disaster and covered mainly the flood damage, a possible damage caused by the typhoon. Flood damage is mainly caused by flooding, and damage is determined by flooding and flow rate, and the results of applying this to low-rise facilities are derived. In addition, the results were derived by applying a method of classification of disaster types in a matrix format to make it easy to see at a glance the connection between disasters caused by damage to a facility. Continuing research in the form presented in this paper will help us identify additional disasters as an occurrence of a disaster.

• Journal of the Korea Convergence Society
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• v.8 no.5
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• pp.13-17
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• 2017

Existing Speech feature extracting method in speech Signal, there are incorrect recognition rates due to incorrect speech which is not clear threshold value. In this article, the modeling method for improving speech recognition performance that combines the feature extraction for speech and silence characteristics normalized to the non-speech. The proposed method is minimized the noise affect, and speech recognition model are convergence of speech signal feature extraction to each speech frame and the silence feature normalization. Also, this method create the original speech signal with energy spectrum similar to entropy, therefore speech noise effects are to receive less of the noise. the performance values are improved in signal to noise ration by the silence feature normalization. We fixed speech and non speech classification standard value in cepstrum For th Performance analysis of the method presented in this paper is showed by comparing the results with CHMM HMM, the recognition rate was improved 2.7%p in the speech dependent and advanced 0.7%p in the speech independent.

• Steel and Composite Structures
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• v.35 no.1
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• pp.77-92
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• 2020

The present paper outlined a procedure for geometrically nonlinear dynamic analysis of functionally graded graphene platelets-reinforced (GPLR-FG) nanocomposite cylinder subjected to mechanical shock loading. The governing equation of motion for large deformation problems is derived using meshless local Petrov-Galerkin (MLPG) method based on total lagrangian approach. In the MLPG method, the radial point interpolation technique is employed to construct the shape functions. A micromechanical model based on the Halpin-Tsai model and rule of mixture is used for formulation the nonlinear functionally graded distribution of GPLs in polymer matrix of composites. Energy dissipation in analyses of the structure responding to dynamic loads is considered using the Rayleigh damping. The Newmark-Newton/Raphson method which is an incremental-iterative approach is implemented to solve the nonlinear dynamic equations. The results of the proposed method for homogenous material are compared with the finite element ones. A very good agreement is achieved between the MLPG and FEM with very fine meshing. In addition, the results have demonstrated that the MLPG method is more effective method compared with the FEM for very large deformation problems due to avoiding mesh distortion issues. Finally, the effect of GPLs distribution on strength, stiffness and dynamic characteristics of the cylinder are discussed in details. The obtained results show that the distribution of GPLs changed the mechanical properties, so a classification of different types and volume fraction exponent is established. Indeed by comparing the obtained results, the best compromise of nanocomposite cylinder is determined in terms of mechanical and dynamic properties for different load patterns. All these applications have shown that the present MLPG method is very effective for geometrically nonlinear analyses of GPLR-FG nanocomposite cylinder because of vanishing mesh distortion issue in large deformation problems. In addition, since in proposed method the distributed nodes are used for discretization the problem domain (rather than the meshing), modeling the functionally graded media yields to more accurate results.

• Journal of IKEEE
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• v.24 no.2
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• pp.475-485
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• 2020

Recently, a crowdsensing system that provides a new sensing service with real-time sensing data provided from a user's device including a sensor without installing a separate sensor has attracted attention. In the crowdsensing system, meaningless data may be provided due to a user's operation error or communication problem, or false data may be provided to obtain compensation. Therefore, the detection and removal of the abnormal data determines the quality of the crowdsensing service. The proposed methods in the past to detect these anomalies are not efficient for the fast-changing environment of crowdsensing. This paper proposes an anomaly data detection method by extracting the characteristics of continuously and rapidly changing sensing data environment by using machine learning technology and modeling it with an appropriate algorithm. We show the performance and feasibility of the proposed system using deep learning binary classification model of supervised learning and autoencoder model of unsupervised learning.

• Journal of the Society of Naval Architects of Korea
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• v.38 no.1
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• pp.116-122
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• 2001

In this paper, to make a base of the fire safety assessment about ship's fire protection design and Classification Society rule, statistical informations and modeling techniques for the fire safety engineering are investigated and probabilistic safety assessment methods in the structural reliability engineering are introduced. FSEM(Fire Safety Evaluation Module) developed in this paper calculates the probability of fatality, which can be used as an index of fire safety. FSEM is used to calculate the probability of fatality of the evacuees in a small room installed according to the rules for fire-proof. Sensitivity analysis is executed to investigate FSEM's applicability to ship. From results, the necessity of new criterion for ship's fire safety design, the need to study the human behavior in the evacuation from fire, and the development of new fire progress model considering special situations in ships are acknowledged.

• Journal of Environmental Science International
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• v.18 no.4
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• pp.423-434
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• 2009

In recent years, the urban thermal environment has become worse, such as days on which the temperature goes above $30^{\circ}C$, sultry nights and heat stroke increase, due to the changes in terrestrial cover such as concrete and asphalt and increased anthropogenic heat emission accompanied by artificial structure. The land use type is an important determinant to near-surface air temperature. Due to these reasons we need to understand and improve the urban thermal environment. In this study, the fifth-generation Pennsylvania State University-National Center for Atmospheric Research Mesoscale Model(MMS) was applied to the metropolitan of Daegu area in order to investigate the influence of land cover changes and urban modifications increase of Albedo to the surface energy budget on the simulated near-surface air temperature and wind speed. The single urban category in existing 24-category U.S. Geological survey land cover classification used in MM5 was divided into 6 classes to account for heterogeneity of urban land cover. As a result of the numerical simulation intended for the metropolitan of Daegu assumed the increase of Albedo of roofs, buildings, or roads, the increase of Albedo (Cool scenario)can make decrease radiation effect of surface, so that it caused drops in ambient air temperature from 0.2 to 0.3 on the average during the daylight hours and smaller (or near-zero) decrease during the night. The Sensible heat flux and Wind velocity is decreased. Modeling studies suggest that increased surface albedo in urban area can reduce surface and air temperatures near the ground and affect related meteorological parameters such as winds, surface air temperature and sensible heat flux.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.4
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• pp.64-75
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• 2008

Since the current database systems for managing geotechnical investigation results were limited by being described boring test result in point feature, it has been trouble for using other GIS data. Although there are some studies for spatial characteristics of subsurface modeling, it is rather lack of being interoperable with GIS, considering geotechnical engineering facts. This is reason for difficulty of practical uses. In this study, we has developed subsurface spatial information model through extracting needed geotechnical engineering data from geotechnical information DB. The developed geotechnical information clustering program(GEOCL) has made a cluster of boring formation(and formation ratio), classification of layer, and strength characteristics of subsurface. The interpolation of boring data has been achieved through zonal kriging method in the consideration of spatial distribution of created cluster. Finally, we make a subsurface spatial information model to integrate with digital elevation model, and visualize 3-dimensional model by subsurface spatial information viewing program(SSIVIEW). We expect to strengthen application capacity of developed model in subsurface interpretation and foundation design of construction works.

• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.4
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• pp.78-88
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• 2003

The land use changes from non-urban areas to urban areas lead to the increased impervious areas, consequently increased direct runoff and higher peak runoff. Urban areas have also been recognized as significant sources of Nonpoint Source (NPS) pollution, while agricultural activities have been known as the primary sources of NPS pollution. Many features of the L-THIA/NPS GIS, L-THIA/NPS WWW system have been enhanced to provide easy-to-use system. The L-THIA model was applied to the Little Eagle Creek (LEC) watershed in Indiana to evaluate the accuracy of the model. The L-THIA/NPS GIS estimated yearly direct runoff values match the direct runoff separated from U.S. Geological Survey stream flow data reasonably. The $R^2$ and Nash-Sutcliffe values are 0.67 and 0.60, respectively. The L-THIA estimated runoff volume and total nitrogen loading for each land use classification in the LEC watershed were computed. The estimated runoff volume and total nitrogen loading in the LEC watershed increased by 180% and 270% for the 20 years. Urbanized areas -"Commercial", "High Density Residential", and "Low Density Residential"- of the LEC watershed made up around 68% of the 1991 total land areas, however contributed more than 92% of average annual runoff and 86% of total nitrogen loading. Therefore, it is essential to consider the impacts of land use change on hydrology and water quality in land use planning of urbanizing watershed.nning of urbanizing watershed.

• Journal of Korean Society of Transportation
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• v.32 no.5
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• pp.522-530
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• 2014

Spatio-temporal congestion evolution pattern can be reproduced using the VDS(Vehicle Detection System) historic speed dataset in the TMC(Traffic Management Center)s. Such dataset provides a pool of spatio-temporally experienced traffic conditions. Traffic flow pattern is known as spatio-temporally recurred, and even non-recurrent congestion caused by incidents has patterns according to the incident conditions. These imply that the information should be useful for traffic prediction and traffic management. Traffic flow predictions are generally performed using black-box approaches such as neural network, genetic algorithm, and etc. Black-box approaches are not designed to provide an explanation of their modeling and reasoning process and not to estimate the benefits and the risks of the implementation of such a solution. TMCs are reluctant to employ the black-box approaches even though there are numerous valuable articles. This research proposes a more readily understandable and intuitively appealing data-driven approach and developes an algorithm for identifying congestion patterns for recurrent and non-recurrent congestion management and information provision.