• Journal of Bio-Environment Control
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• v.31 no.2
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• pp.98-103
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• 2022

Non-destructive estimation of leaf area is a more efficient and convenient method than leaf excision. Thus, several models predicting leaf area have been developed for various horticultural crops. However, there are limited studies on estimating the leaf area of strawberry plants. In this study, we predicted the leaf areas via nonlinear regression analysis using the leaf lengths and widths of three-compound leaves in five domestic strawberry cultivars ('Arihyang', 'Jukhyang', 'Keumsil', 'Maehyang', and 'Seollhyang'). The coefficient of determination (R²) between the actual and estimated leaf areas varied from 0.923 to 0.973. The R² value varied for each cultivar; thus, leaf area estimation models must be developed for each cultivar. The leaf areas of the three cultivars 'Jukhyang', 'Seolhyang', and 'Maehyang' could be non-destructively predicted using the model developed in this study, as they had R² values over 0.96. The cultivars 'Arihyang' and 'Geumsil' had slightly low R² values, 0.938 and 0.923, respectively. The leaf area estimation model for each cultivar was coded in Python and is provided in this manuscript. The estimation models developed in this study could be used extensively in other strawberry-related studies.

• Journal of Advanced Navigation Technology
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• v.24 no.3
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• pp.192-197
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• 2020

Recently, the technologies related to autonomous drive has studying the goal for safe operation and prevent accidents of vehicles. There is radar and camera technologies has used to detect obstacles in these autonomous vehicle research. Now a day, the method for using LiDAR sensor has considering to detect nearby objects and accurately measure the separation distance in the autonomous navigation. It is calculates the distance by recognizing the time differences between the reflected beams and it allows precise distance measurements. But it also has the disadvantage that the recognition rate of object in the atmospheric environment can be reduced. In this paper, point cloud data by triangular functions and Line Regression model are used to implement measurement algorithm, that has improved detecting objects in real time and reduce the error of measuring separation distances based on improved reliability of raw data from LiDAR sensor. It has verified that the range of object detection errors can be improved by using the Python imaging library.

• Journal of Korean Tunnelling and Underground Space Association
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• v.18 no.6
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• pp.545-556
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• 2016

If a back analysis is used in various measurement information for the estimation of an operating subsea tunnel safety, it is possible to obtain the results within efficient error rate. With such a commercial geotechnical analysis program as FLAC3D, back analysis is performed with a DEA which was validated in previous studies. However, there is a problem that is relatively a time-consuming analysis. For this reason, beam-spring model-based FEM solver which takes shorter relative analysis time, was developed by Python language, and then combined with the built-DEA. In order to consider the assessment of safety of an operation tunnel near real-time, a program for longitudinal direction tunnel was developed due to its relative easy development for analysis solver engine.

• Journal of Internet of Things and Convergence
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• v.2 no.3
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• pp.1-6
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• 2016

This paper aims to present the physical computing learning model applicable in teaching the information and communication technology for technology and engineering education. This model is based on the physical computing and deals with the information creation and information transfer in one framework, thus provides students with the total understanding and practice opportunity about information and communication. The proposed learning models are classified into the client-server based model and the web based model. In the implemented learning model, the acquirement and control of information is performed by sketch on Arduino and the communication of information is performed by the Python socket on Raspberry Pi well known as an education platform. Our proposed learning model can be used for teaching students to understand the concept of Internet of Things (IoT), which provides us with world wide control and communication of information.

• Composites Research
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• v.25 no.5
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• pp.136-140
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• 2012

This paper describes the bone healing process of fractured long bones such as a tibia applied by composite IM rods using finite element analysis. To simulated tissue differentiation process mechano-regulation theory with a deviatoric strain was implemented and a user's subroutine programmed by a Python code for an iterative calculation was used. To broadly find the appropriate rod modulus for healing bone fractures, composite IM rods were analyzed considering the stacking sequence. To compare mechanical stimulation at fracture gap, two kinds of initial loading conditions were applied. As a result, it was found that the initial loading condition was the most sensitive factor for the healing performance. In case a composite IM rod made of a plain weave carbon fiber/epoxy (WSN3k) had a stacking sequence of $[{\pm}45]_{nT}$, the healing efficiency was the most effective under a initial load of 10%BW.

• Structural Engineering and Mechanics
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• v.72 no.6
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• pp.713-722
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• 2019

Micromechanics is a technique for the analysis of composites or heterogeneous materials which focuses on the components of the intended structure. Each one of the components can exhibit isotropic behavior, but the microstructure characteristics of the heterogeneous material result in the anisotropic behavior of the structure. In this research, the general mechanical properties of a 3D anisotropic and heterogeneous Representative Volume Element (RVE), have been determined by applying periodic boundary conditions (PBCs), using the Asymptotic Homogenization Theory (AHT) and strain energy. In order to use the homogenization theory and apply the periodic boundary conditions, the ABAQUS scripting interface (ASI) has been used along with the Python programming language. The results have been compared with those of the Homogeneous Boundary Conditions method, which leads to an overestimation of the effective mechanical properties. According to the results, applying homogenous boundary conditions results in a 33% and 13% increase in the shear moduli G₂₃ and G₁₂, respectively. In polymeric composites, the fibers have linear and brittle behavior, while the resin exhibits a non-linear behavior. Therefore, the nonlinear effects of resin on the mechanical properties of the composite material is studied using a user-defined subroutine in Fortran (USDFLD). The non-linear shear stress-strain behavior of unidirectional composite laminates has been obtained. Results indicate that at arbitrary constant stress as 80 MPa in-plane shear modulus, G₁₂, experienced a 47%, 41% and 31% reduction at the fiber volume fraction of 30%, 50% and 70%, compared to the linear assumption. The results of this study are in good agreement with the analytical and experimental results available in the literature.

• The Bulletin of The Korean Astronomical Society
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• v.38 no.1
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• pp.74-74
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• 2013

Multi-purpose Infra-Red Imaging System (MIRIS) is the main payload of the Science and Technology Satellite-3 (STSAT-3) to be launched in the late half of this year. For the Space Observation Camera (SOC) of MIRIS, we developed the data reduction pipeline with Python powered by Astropy, a community Python library for astronomy. The pipeline features the following functionalities: i) to retrieve the raw observation data from database and convert it to a FITS format, ii) to mask bad pixels, iii) to correct the non-linearity, iv) to differentiate the frames, v) to correct the flat-field, vi) to correct focal-plane distortion, vii) to improve the world coordinate system (WCS) information using known point-source catalog, and viii) to combine the sequentially taken frames. The pipeline is well modularized and has flexibility for later update. In this poster, we introduce the details of the pipeline's features and the future maintenance plan.

• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.2
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• pp.195-212
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• 2017

When back analysis is used for the assessment of an operating subsea tunnel safety in various measurement information such as stress, water pressure and tunnel lining and ground stiffness degradation, the reliable results within tolerable error rate can be obtained. By utilizing a commercial geotechnical analysis program FLAC3D, back analysis can be performed with a DEA which has already been successfully validated in previous studies. However, relative more time-consumption is the drawback of this approach. For this reason, this study introduced beam-spring model-based on FEM solver which uses less analysis time relatively. Beam-spring program capable of structural analysis of a circular tunnel section was developed by using Python language and combined with the built-DEA. From the measurement datum, expected to estimate the stability of an operation tunnel close to real-time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.3
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• pp.548-556
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• 2018

NMS (Network Management System) is a system that is used for a small or large networks management. As the size of network becomes larger and the configuration information become complicated, it becomes more difficult to grasp the network status and it takes much time to diagnose the failure of the network equipment. In this paper, to alleviate the problems of NMS we implement web-based network topology automatically using JavaScript, Python, HTML5 based TWaver. The detailed implementation of the system include the automatic collection of the connection information based on the equipment information registered in the NMS system, the implementation of the web-based network topology and the remote fault diagnosis. In the network topology, we can expect to improve the quality of the NMS system through structured data management by adding the configuration management, fault management and performance management functions in a comprehensive manner.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.471-483
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• 2021

The purpose of this study is to find out audience' response of virtual influencer at the starting line of virtual influencer marketing. Therefore, posts, comments, number of likes, and video reviews were collected from Instagram of virtual influencers active in Korea. Python 3.7 and Textom were used for data collection and analysis. Sentimental analysis showed that the rate of positivity was higher than the rate of negativity and neutrality. The appearance of virtual influencer was found to be a major factor in both positive and negative. Consumers' interest in virtual influencer could be inferred from the neutral sensibility. This study is meaningful in that it presented data to help establish strategies for virtual influencer marketing by examining consumer reactions to virtual influencer and identifying factors of positive and negative emotions toward virtual influencer.