• Title/Summary/Keyword: Computing Costs

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A Study on the Metadata Schema for the Collection of Sensor Data in Weapon Systems (무기체계 CBM+ 적용 및 확대를 위한 무기체계 센서데이터 수집용 메타데이터 스키마 연구)

  • Jinyoung Kim;Hyoung-seop Shim;Jiseong Son;Yun-Young Hwang
    • Journal of Internet Computing and Services
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    • v.24 no.6
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    • pp.161-169
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    • 2023
  • Due to the Fourth Industrial Revolution, innovation in various technologies such as artificial intelligence (AI), big data (Big Data), and cloud (Cloud) is accelerating, and data is considered an important asset. With the innovation of these technologies, various efforts are being made to lead technological innovation in the field of defense science and technology. In Korea, the government also announced the "Defense Innovation 4.0 Plan," which consists of five key points and 16 tasks to foster advanced science and technology forces in March 2023. The plan also includes the establishment of a Condition-Based Maintenance system (CBM+) to improve the operability and availability of weapons systems and reduce defense costs. Condition Based Maintenance (CBM) aims to secure the reliability and availability of the weapon system and analyze changes in equipment's state information to identify them as signs of failure and defects, and CBM+ is a concept that adds Remaining Useful Life prediction technology to the existing CBM concept [1]. In order to establish a CBM+ system for the weapon system, sensors are installed and sensor data are required to obtain condition information of the weapon system. In this paper, we propose a sensor data metadata schema to efficiently and effectively manage sensor data collected from sensors installed in various weapons systems.

The Economic Effects of Tax Incentives for Housing Owners: An Overview and Policy Implications (주택소유자(住宅所有者)에 대한 조세감면(租稅減免)의 경제적(經濟的) 효과(效果) : 기존연구(旣存硏究)의 개관(槪觀) 및 정책시사점(政策示唆點))

  • Kim, Myong-sook
    • KDI Journal of Economic Policy
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    • v.12 no.2
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    • pp.135-149
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    • 1990
  • Housing owners in Korea have a variety of tax advantages such as income tax exemption for the imputed rent of owner-occupied housing, exemption from the capital gains tax and deduction of the estate tax for one-house households. These tax reliefs for housing owners not only conflict with the principle of horizontal and vertical equity, but also lead to resource misallocation by distorting the housing market, and thus bring about regressive distribution effects. Particularly in the case of Korea with its imperfect capital market, these measures exacerbate the inter-class inequality of housing ownership as well as inequalities in wealth, by causing the affluent to demand needlessly large housing, while the poor and young experience difficulties in purchasing residential properties. Therefore, the Korean tax system must be altered as follows in order to disadvantage owner-occupiers, especially those owners of luxury housing. These alterations will promote housing-ownership, tax burden equity, efficiency of resource allocation, as well as the desirable distribution of income. First, income tax deductions for the rent payments of tenants are recommended. Ideally, the way of recovering the fiscal equivalence between the owner-occupiers and tenants is to levy an income tax on the former's imputed rents, and if necessary to give them tax credits. This, however, would be very difficult from a practical viewpoint, because the general public may perceive the concept of "imputed rent" as cumbersome. Computing the imputed rent also entails administrative costs, rendering quite reasonable, the continued exemption of imputed rent from taxation with the simultaneous deduction in the income tax for tenants. This would further enhance the administrative efficiency of income tax collection by easing assessment of the landlord's income. Second, a capital gains tax should be levied on the one-house household, except with the postponement of payments in the case that the seller purchases higher priced property. Exemption of the capital gains tax for the one-house household favors those who have more expensive housing, providing an incentive to the rich to hold even larger residences, and to the constructors to build more luxurious housing to meet the demand. So it is not desirable to sustain the current one-house household exemption while merely supplementing it with fastidious measures. Rather, the rule must be abolished completely with the concurrent reform of the deduction system and lowering of the tax rate, measures which the author believes will help optimize the capital gains tax incidence. Finally, discontinuation of the housing exemption for the heir is suggested. Consequent increases in the tax burden of the middle class could be mitigated by a reduction in the rate. This applies to the following specific exemptions as well, namely, for farm lands, meadows, woods, business fields-to foster horizontal equity, while denying speculation on land that leads to a loss in allocative efficiency. Moreover, imperfections in the Korean capital market have disallowed the provision of long term credit for housing seekers. Remedying these problems is essential to the promotion of greater housing ownership by the low and middle income classes. It is also certain that a government subsidy be focused on the poorest of the poor who cannot afford even to think of owning a housing.

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Regeneration of a defective Railroad Surface for defect detection with Deep Convolution Neural Networks (Deep Convolution Neural Networks 이용하여 결함 검출을 위한 결함이 있는 철도선로표면 디지털영상 재 생성)

  • Kim, Hyeonho;Han, Seokmin
    • Journal of Internet Computing and Services
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    • v.21 no.6
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    • pp.23-31
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    • 2020
  • This study was carried out to generate various images of railroad surfaces with random defects as training data to be better at the detection of defects. Defects on the surface of railroads are caused by various factors such as friction between track binding devices and adjacent tracks and can cause accidents such as broken rails, so railroad maintenance for defects is necessary. Therefore, various researches on defect detection and inspection using image processing or machine learning on railway surface images have been conducted to automate railroad inspection and to reduce railroad maintenance costs. In general, the performance of the image processing analysis method and machine learning technology is affected by the quantity and quality of data. For this reason, some researches require specific devices or vehicles to acquire images of the track surface at regular intervals to obtain a database of various railway surface images. On the contrary, in this study, in order to reduce and improve the operating cost of image acquisition, we constructed the 'Defective Railroad Surface Regeneration Model' by applying the methods presented in the related studies of the Generative Adversarial Network (GAN). Thus, we aimed to detect defects on railroad surface even without a dedicated database. This constructed model is designed to learn to generate the railroad surface combining the different railroad surface textures and the original surface, considering the ground truth of the railroad defects. The generated images of the railroad surface were used as training data in defect detection network, which is based on Fully Convolutional Network (FCN). To validate its performance, we clustered and divided the railroad data into three subsets, one subset as original railroad texture images and the remaining two subsets as another railroad surface texture images. In the first experiment, we used only original texture images for training sets in the defect detection model. And in the second experiment, we trained the generated images that were generated by combining the original images with a few railroad textures of the other images. Each defect detection model was evaluated in terms of 'intersection of union(IoU)' and F1-score measures with ground truths. As a result, the scores increased by about 10~15% when the generated images were used, compared to the case that only the original images were used. This proves that it is possible to detect defects by using the existing data and a few different texture images, even for the railroad surface images in which dedicated training database is not constructed.

A Method of Reproducing the CCT of Natural Light using the Minimum Spectral Power Distribution for each Light Source of LED Lighting (LED 조명의 광원별 최소 분광분포를 사용하여 자연광 색온도를 재현하는 방법)

  • Yang-Soo Kim;Seung-Taek Oh;Jae-Hyun Lim
    • Journal of Internet Computing and Services
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    • v.24 no.2
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    • pp.19-26
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    • 2023
  • Humans have adapted and evolved to natural light. However, as humans stay in indoor longer in modern times, the problem of biorhythm disturbance has been induced. To solve this problem, research is being conducted on lighting that reproduces the correlated color temperature(CCT) of natural light that varies from sunrise to sunset. In order to reproduce the CCT of natural light, multiple LED light sources with different CCTs are used to produce lighting, and then a control index DB is constructed by measuring and collecting the light characteristics of the combination of input currents for each light source in hundreds to thousands of steps, and then using it to control the lighting through the light characteristic matching method. The problem with this control method is that the more detailed the steps of the combination of input currents, the more time and economic costs are incurred. In this paper, an LED lighting control method that applies interpolation and combination calculation based on the minimum spectral power distribution information for each light source is proposed to reproduce the CCT of natural light. First, five minimum SPD information for each channel was measured and collected for the LED lighting, which consisted of light source channels with different CCTs and implemented input current control function of a 256-steps for each channel. Interpolation calculation was performed to generate SPD of 256 steps for each channel for the minimum SPD information, and SPD for all control combinations of LED lighting was generated through combination calculation of SPD for each channel. Illuminance and CCT were calculated through the generated SPD, a control index DB was constructed, and the CCT of natural light was reproduced through a matching technique. In the performance evaluation, the CCT for natural light was provided within the range of an average error rate of 0.18% while meeting the recommended indoor illumination standard.