• The Research Journal of the Costume Culture
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• v.27 no.5
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• pp.415-432
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• 2019

The purpose of the present study was to generate a list of business ethics components according to business area for small and medium-sized fashion companies. Based on the literature review, 21 components of business ethics components were identified within five business areas. Ten CEOs(Chief Executive Officers) each participated in an in-depth interview, sharing ethical and unethical cases from their own businesses. Constant comparative analysis was used to generate important business ethics components from those cases. In results, important business ethics components for each business area are: 1) using human-friendly materials, strengthening sustainable technologies, using vegan materials, concerning safe process, and reducing waste in the material production and sourcing area, 2) enhancing an efficiency in design, developing recycle/reuse designs, avoiding to copy designs, and using messages for public interest in the product design area, 3) concerning fair-trade, reducing harmful substance, saving energy, and using ethical supply channels in the distribution and logistics area, 4) acquiring certifications, promoting consumer protection, avoiding exaggerative/false advertisements, and promoting social contributions in the management and marketing area, and 5) promoting workers' rights, complying with the law, and investing on employee educations in the labor management area. All of the ethical and unethical cases of the ten companies have involved aspects of the 21 components, thereby enhancing understandings on how each issue is being seriously considered and/or handled in the small and medium-sized fashion companies. Study findings may provide a basis for development of a research model for quantitative studies and/or educational programs related to business ethics in the fashion industry.

• Steel and Composite Structures
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• v.31 no.1
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• pp.13-25
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• 2019

Reactive powder concrete (RPC) is a type of ultra-high strength concrete that has a relatively high brittleness. However, its ductility can be improved by confinement, and the use of RPC in composite RPC filled steel tube columns has become an important subject of research in recent years. This paper aims to present an experimental study of axial capacity calculation of RPC filled circular steel tube columns. Twenty short columns under axial compression were tested and information on their failure patterns, deformation performance, confinement mechanism and load capacity were presented. The effects of load conditions, diameter-thickness ratio and compressive strength of RPC on the axial behavior were further discussed. The experimental results show that: (1) specimens display drum-shaped failure or shear failure respectively with different confinement coefficients, and the load capacity of most specimens increases after the peak load; (2) the steel tube only provides lateral confinement in the elastic-plastic stage for fully loaded specimens, while the confinement effect from steel tube initials at the set of loading for partially loaded specimens; (3) confinement increases the load capacity of specimens by 3% to 38%, and this increase is more pronounced as the confinement coefficient becomes larger; (4) the residual capacity-to-ultimate capacity ratio is larger than 0.75 for test specimens, thus identifying the composite columns have good ductility. The working mechanism and force model of the composite columns were analyzed, and based on the twin-shear unified strength theory, calculation methods of axial capacity for columns with two load conditions were established.

• Composites Research
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• v.31 no.6
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• pp.429-434
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• 2018

We investigate strain transmissions of a surface bonded distributed optical fiber sensor considering strain variation according to positions. We first derive a strain transmission ratio depending on a wavelength of a strain distribution of the host structure from an analysis model. The strain transmission ratio is compared with numerical results obtained from the finite element method using ABAQUS. We find that the analytical results agree well with the numerical results. The strain transmission ratio is a function of a wavelength, i.e. the strain transmission ratio decreases (increases) as the wavelength of the host strain decreases (increases). Therefore, if an arbitrary strain distribution containing various wavelengths is given to a host structure, a distorted strain distribution will be observed in the distributed optical fiber sensor compare to that of the host structure, because each wavelength shows different strain transmission ratio. The strain transmission ratio derived in this study will be useful for accurately identifying the host strain distribution based on the signal of a distributed optical fiber sensor.

• Journal of Korean Society of Rural Planning
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• v.27 no.3
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• pp.35-46
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• 2021

Ecosystem services play a role in promoting sustainable development by contributing to human welfare. For sustainable development, a balance between supply and demand for ecosystem services must be made. In this regard, in this study, factor analysis was performed using the results of measuring ecosystem services for the supply of ecosystem services and national statistical data representing socio-economic factors for demand for ecosystem services The results of analysis for Gyeong-gi Province are as follows. The service supply based on the result of ecosystem services was divided into the mixed service provisioning as factor1, the food provisioning as factor2, and the P retention service provisioning area as factor3. As for the demand for services based on socio-economic factors, factor1 is divided into urbanized areas, factor2 is forest development area, and factor3 is agricultural activity development area. Local governments that maintain balance were evaluated as Pocheon, Yangpyeong, Icheon, Pyeongtaek, Goyang, Suwon, Gwangmyeong, and Osan, and imbalanced local governments appeared in Gimpo, Uiwang, Anseong, and Yeoju. A management plan to maintain the balance between supply and demand of ecosystem services was suggested. The analysis method and results of this study are expected to be applicable to various local governments through regional expansion.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.8
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• pp.311-318
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• 2021

Research has been ongoing to detect ships from offshore photographs for a variety of reasons, including maritime security, identifying international trends, and social scientific research. Due to the development of artificial intelligence, R-CNN models for object detection in photographs and images have emerged, and the performance of object detection has risen dramatically. Ship detection in offshore photographs using the R-CNN model has also begun to apply to satellite photography. However, satellite images project large areas, so various objects such as vehicles, landforms, and buildings are sometimes recognized as ships. In this paper, we propose a novel methodology to improve the performance of ship detection in satellite photographs using R-CNN series models. We separate land and sea via marker-based watershed algorithm and perform morphology operations to specify RoI one more time, then detect vessels using R-CNN family models on specific RoI to reduce typology. Using this method, we could reduce the misdetection rate by 80% compared to using only the Fast R-CNN.

• Korean Journal of Agricultural Science
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• v.47 no.4
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• pp.1159-1168
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• 2020

The conduits of agricultural reservoirs undergo deterioration over a considerable period of time and this is highly likely to cause structural problems such as cracks. It is therefore important to consider the effects of structural defects on the body from the viewpoint of stability and maintenance of the embankment. In this study, basic data on the effects of the crack location on the stability of the embankment is obtained by identifying, comparing, and analyzing the erosion characteristics and pore water pressure behavior through a large-scale model experiment that involves classifying the location of the conduit cracks. From the results of the experiment, it was confirmed that when a crack occurred, the amount of leakage increased as the location of the crack portion was closer to the water level, and the internal erosion phenomenon accelerated, thereby increasing the possibility of piping. It was also found that an upstream conduit crack affects the erosion and water pressure change of the central and downstream conduit of the embankment, and the conduit crack has a very large effect on the pore water pressure despite the low upstream water level. Therefore, the seepage behavior of the embankment for each conduit crack identified in this study is considered to be useful basic data for preparing a repair and reinforcement plan according to the crack location in the future.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.58-73
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• 2021

Cloud Service Providers (CSPs) enable their users to access Cloud computing and storage services from anywhere in quick and flexible manners through the Internet. With the basis of 'pay-as-you-go' model, it makes the interactions between CSPs and the users play a vital role in shaping the Cloud computing market. A pool of virtualized and dynamically scalable Cloud services that delivered on demand to the users is associated with guaranteed performance and cost-provisioning. It needed a costing scheme for determining suitable charges in order to secure lease pricing of the Cloud services. However, it is hard to meet the satisfied prices for both CSPs and users due to their conflicting needs. Furthermore, there is lack of Service Level Agreements (SLAs) that allowing the users to take part into price negotiating process. The users may lose their interest to use Cloud services while reducing CSPs profit. Therefore, this paper proposes a generic costing scheme for Cloud services using General Equilibrium Theory (GET). GET helps to formulate the price function for various services' factors to match with various demands from the users. It is initially determined by identifying the market circumstances that a general equilibrium will be hold and reached. Specifically, there are two procedures of agreement made in response to (i) established equilibrium supply and demand, and (ii) service price formed and constructed in a price range. The SLAs in our costing scheme is integrated to satisfy both CSPs and users' needs while minimizing their conflicts. The price ranging strategy is deliberated to provide prices' options to the users with respect their budget limit. Meanwhile, the CSPs can adaptively charge based on users' preferences without losing their profit. The costing scheme is testable and analyzed in multi-tenant computing environments. The results from our simulation experiments demonstrate that the proposed costing scheme provides better users' satisfaction while fostering fairness pricing in the Cloud market.

• Journal of the Korea Society of Computer and Information
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• v.26 no.7
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• pp.109-118
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• 2021

Different from previous studies, this study focuses on accommodation providers' personalization services and platform convenience variables, identifying how these prior factors affect perceived value and trust in accommodation services on a shared homestay platform, and how consumers' innovation plays a role in the process. Through this, we would like to identify the mechanism of interaction between accommodation service providers and consumers mediated by the shared homestay platform and present implications for a more customer-centered platform operation strategy. This study has an extended meaning for prior research, empirically confirming that the increase in personalized offline service quality of personalized hosts in shared economic models has a positive impact on perceived value and platform trust of consumers. At the same time, we confirm that under the shared economy model, consumers' innovation propensity plays an important positive role in regulating their perceived value aspects as well as their confidence in the platform.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.5
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• pp.1610-1629
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• 2021

Failures frequently occurred in manufacturing machines due to complex and changeable manufacturing environments, increasing the downtime and maintenance costs. This manuscript develops a novel deep learning-based method named Multi-Domain Convolutional Neural Network (MDCNN) to deal with this challenging task with vibration signals. The proposed MDCNN consists of time-domain, frequency-domain, and statistical-domain feature channels. The Time-domain channel is to model the hidden patterns of signals in the time domain. The frequency-domain channel uses Discrete Wavelet Transformation (DWT) to obtain the rich feature representations of signals in the frequency domain. The statistic-domain channel contains six statistical variables, which is to reflect the signals' macro statistical-domain features, respectively. Firstly, in the proposed MDCNN, time-domain and frequency-domain channels are processed by CNN individually with various filters. Secondly, the CNN extracted features from time, and frequency domains are merged as time-frequency features. Lastly, time-frequency domain features are fused with six statistical variables as the comprehensive features for identifying the fault. Thereby, the proposed method could make full use of those three domain-features for fault diagnosis while keeping high distinguishability due to CNN's utilization. The authors designed massive experiments with 10-folder cross-validation technology to validate the proposed method's effectiveness on the CWRU bearing data set. The experimental results are calculated by ten-time averaged accuracy. They have confirmed that the proposed MDCNN could intelligently, accurately, and timely detect the fault under the complex manufacturing environments, whose accuracy is nearly 100%.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.531-542
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• 2021

This study was undertaken for identifying ways to positively resolve problems associated with perceived overqualification from the perspective of job crafting, which is highlighted as a social issue in the labor market. We hypothesized the mediating role of job crafting in order to uncover the questions regarding when and how perceived overqualification associates with an employee's organizational commitment. Autoregressive cross-lagged models were applied to the longitudinal data gathered from 263 full-time employees across 3 waves over 9 months. Our results demonstrate positive and significant cross-lagged effect of perceived overqualification on job crafting and organizational commitment. However, the cross-lagged effect of job crafting on perceived overqualification was found to be insignificant, but was significant for organizational commitment. There were no other indications of reverse causation effects. Our data indicates that job crafting longitudinally mediates the relation between perceived overqualification and organizational commitment. These findings offer a meaningful implication that employees who perceive themselves to be overqualified should be given an opportunity to craft their own jobs.