• Journal of the Korea Society of Computer and Information
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• v.20 no.6
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• pp.107-115
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• 2015

A fine is defined to the criminal penalty which is slighter than imprisonment on a system of criminal penalty, but put practically a seat to imprisonment and similar strong discipline contrivance to commission agent in capitalism societies be doing. Also, did heavy commission, but the corporation time, a fine to consider the respect which cannot impose other criminal penalty, and cannot but impose fine penalty only to this corporation carries out art as important criminal penalty than the commission which a person does. But fine drawing of our country cannot carry out art scaring to criminal penalty to rich body as aggregate fine drawing, and a lot of, but do abatement duration of a fine so as same, and be most in spite of adjudication criminal sentence occupying at criminal case adjudication, and difference cannot do to an amount of a fine that is carrying well out the art. Therefore, and have to change to the daily fine systemdm which gained because of total fine system in order to carry out value as modern criminal penalty, and a few fines shall exchange to penalty payment system according to complement department canon of Penal Code, and social accusation protects individual information of low commission agent if so, can normally do art accomplishment of criminal penalty. The system that the maximum can guarantee right of defence of accused has to have to be introduced in procedural a few aspect to pronounce this and a fine. Specially, let explain necessary fact to be related to, and informal procedures understand, and introduction of drawing to be able to get from accord of accused is necessary for accused before charging to informal decree in order cannot be guaranteed right of defence this of accused while consisting in writing of whether accusation and adjudication are procedural at informal procedures, and to supplement respect.

• Atmosphere
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• v.24 no.1
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• pp.101-110
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• 2014

This study estimates and evaluates the daily January temperature from 2003 to 2012 with 30 m-resolution over South Korea, using a modified Parameter-elevation Regression on Independent Slopes Model (K-PRISM). Several factors in K-PRISM are also adjusted to 30 m grid spacing and daily time scales. The performance of K-PRISM is validated in terms of bias, root mean square error (RMSE), and correlation coefficient (Corr), and is then compared with that of inverse distance weighting (IDW) and hypsometric methods (HYPS). In estimating the temperature over Jeju island, K-PRISM has the lowest bias (-0.85) and RMSE (1.22), and the highest Corr (0.79) among the three methods. It captures the daily variation of observation, but tends to underestimate due to a high-discrepancy in mean altitudes between the observation stations and grid points of the 30 m topography. The temperature over South Korea derived from K-PRISM represents a detailed spatial pattern of the observed temperature, but generally tends to underestimate with a mean bias of -0.45. In bias terms, the estimation ability of K-PRISM differs between grid points, implying that care should be taken when dealing with poor skill area. The study results demonstrate that K-PRISM can reasonably estimate 30 m-resolution temperature over South Korea, and reflect topographically diverse signals with detailed structure features.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.32-38
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• 2023

This study investigates the influence of particulate matter concentrations on the incidence of asthma, focusing on the delayed onset of symptoms and subsequent medical consultations. Analysis incorporates a four-day lag from the initiation of fine dust exposure and compares asthma patterns before and after the World Health Organization's (WHO) classification of fine dust as a Group 1 carcinogen in November 2013. Utilizing daily PM10 data and asthma-related medical visit counts in Seoul from 2008 to 2016, the study additionally incorporates Google search frequencies and newspaper article counts on fine dust to assess public awareness. Results reveal a surge in search frequencies and article publications after WHO announcement, indicating heightened public interest. To standardize the long-term asthma occurrence trend, the daily asthma patient numbers are ratio-adjusted based on annual averages. The analysis uncovers an increase in asthma medical visits 2 to 3 days after fine dust events. Additionally, greater public awareness of fine dust hazards correlates with a significant reduction in asthma occurrence after such events, even within 'normal' fine dust concentrations. Notably, behavioral changes, like limiting outdoor activities, contribute to this decrease. This study highlights the importance of analyzing accumulated medical data over an extended period to identify general public behavioral patterns, deviating from conventional survey methods in social sciences. Future research aims to extend data collection beyond 2016, exploring recent trends and considering the potential impact of decreased fine dust awareness amid the COVID-19 pandemic.

• Atmosphere
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• v.33 no.3
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• pp.319-330
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• 2023

As the need for PM type observation increases, Surface Particulate Matter Network (SPARTAN), PM samplers analyzes aerosol samples for PM mass concentration and chemical composition, were recently installed at two sites: Yonsei University at Seoul and Ulsan Institute of Science and Technology (UNIST) at Ulsan. These SPARTAN filter samplers and nephelometers provide the PM_2.5 mass concentration and chemical speciation data with aerosol type information. We introduced the overall information and installation of SPARTAN at the field site in this study. After installation and observation, both Seoul and Ulsan sites showed a similar time series pattern with the daily PM_2.5 mass concentration of SPARTAN and the data of Airkorea. In particular, in the case of high concentrations of fine particles, daily average value of PM_2.5 was relatively well-matched. During the Yonsei University observation period, high concentrations were displayed in the order of sulfate, black carbon (BC), ammonium, and calcium ions on most measurement days. The case in which the concentration of nitrate ions showed significant value was confirmed as the period during which the fine dust alert was issued. From the data analysis, SPARTAN data can be analyzed in conjunction with the existing urban monitoring network, and it is expected to have a synergetic effect in the research field. Additionally, the possibility of being analyzed with optical data such as AERONET is presented. In addition, the method of installing and operating SPARTAN has been described in detail, which is expected to help set the stage for the observation system in the future.

• Journal of Korean Society of Forest Science
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• v.95 no.2
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• pp.160-167
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• 2006

Most of the forest fires that occur in South Korea are caused by human. We partitioned South Korea into nine districts and used observed weather data and daily fire occurrence records for the 1994 to 2003 period to develop a human-caused fire occurrence model of South Korea. Logistic regression analysis techniques were used to relate the probability of a fire day to Fine Fuel Moisture Code (FFMC) component of the Canadian Forest Fire Danger Rating System. The probability of the number of fire day was increased as FFMC increased in the nine districts of South Korea.

• Journal of Platform Technology
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• v.9 no.4
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• pp.79-89
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• 2021

In this paper, the fine dust (PM10) and ultrafine dust (PM2.5) measurement platforms are designed to be mobile and fixed using oneM2M, the international standard for IoT. The fine dust measurement platform is composed and designed with a fine dust measurement device, agent, oneM2M platform, oneM2M IPE, and monitoring system. The main difference between mobile and fixed is that the mobile uses the MQTT protocol for interconnection between devices and services without blind spots based on LTE connection, and the fixed uses the LoRaWAN protocol with low power and wide communication range. Not only fine dust, but also temperature, humidity, atmospheric pressure, volatile organic compounds (VOC), carbon monoxide (CO), sulfur dioxide (SO2), nitrogen dioxide (NO2), and noise data related to daily life were collected. The collected sensor values were managed using the common API provided by oneM2M through the agent and oneM2M IPE, and it was designed into four resource types: AE and container. Six functions of operability, flexibility, convenience, safety, reusability, and scalability were analyzed through the fine dust measurement platform design.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.5
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• pp.423-432
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• 2018

Surface water mapping has been widely used in various remote sensing applications. Water indices have been commonly used to distinguish water bodies from land; however, determining the optimal threshold and discriminating water bodies from similar objects such as shadows and snow is difficult. Deep learning algorithms have greatly advanced image segmentation and classification. In particular, FCN (Fully Convolutional Network) is state-of-the-art in per-pixel image segmentation and are used in most benchmarks such as PASCAL VOC2012 and Microsoft COCO (Common Objects in Context). However, these data sets are designed for daily scenarios and a few studies have conducted on applications of FCN using large scale remotely sensed data set. This paper aims to fine-tune the pre-trained FCN network using the CRMS (Coastwide Reference Monitoring System) data set for surface water mapping. The CRMS provides color infrared aerial photos and ground truth maps for the monitoring and restoration of wetlands in Louisiana, USA. To effectively learn the characteristics of surface water, we used pre-trained the DeepWaterMap network, which classifies water, land, snow, ice, clouds, and shadows using Landsat satellite images. Furthermore, the DeepWaterMap network was fine-tuned for the CRMS data set using two classes: water and land. The fine-tuned network finally classifies surface water without any additional learning process. The experimental results show that the proposed method enables high-quality surface mapping from CRMS data set and show the suitability of pre-trained FCN networks using remote sensing data for surface water mapping.

• Journal of Korean Society for Atmospheric Environment
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• v.19 no.2
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• pp.167-177
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• 2003

The number size distribution of urban aerosols ranging from 0.02 to 20 ${\mu}{\textrm}{m}$ in diameter was measured by using a scanning mobility particle sizer (SMPS) system and an aerodynamic particle sizer spectrometer (APS) at Seoul from November 30,2001 to January 14, 2002. The gaseous species such as CO, NO, NO$_2$, and $O_3$ were also continuously monitored. The daily average concentration of urban aerosols sorted into three groups (0.02~0.1 ${\mu}{\textrm}{m}$, 0.1~1 ${\mu}{\textrm}{m}$ and 1~10 ${\mu}{\textrm}{m}$) and the typical number, surface, and volume distributions of urban aerosols were discussed in this paper. The weekly variation of aerosol concentration was compared with those of gaseous concentrations. relative humidity, and visibility. The results showed that the particle number concentration seemed to increase in the morning and the number concentration of fine particles less than 1 fm in diameter seemed to increase when the concentrations of CO, NO, and NO$_2$ were high. The number concentration of fine particles was relatively high when the relative humidity was greater than 70％ during the increasing period of relative humidity. The visibility was weakly correlated with the concentration of aerosols ranging 0.1 to 1 ${\mu}{\textrm}{m}$, and the number size distribution for high visibility episode was apparently different from that for low visibility episode.

• Journal of the Korean Society of Industry Convergence
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• v.20 no.4
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• pp.339-343
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• 2017

Masks are a portable functional product for daily use. They can protect user health by filtering harmful fine particles in the air. In the past decade, there have been approximately 10 yellow dust incidences per year, amounting to a total duration of 20 days, and they continue to increase year after year. In addition, the frequency of yellow dust incidences in Korea has increased by more than four times compared to levels from the 1970s. Statistical reports indicate that annual damages caused by yellow dust amount to more than six trillion KRW. This study developed a zero-fog multi-layer mask with a collection efficiency and yellow dust and particulate matter filtration areas that are at least thrice as effective as existing masks. The new mask also reduces pressure drag by half.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.6
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• pp.2377-2397
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• 2020

Human activity recognition is widely used in smart homes, health care and indoor monitor. Traditional approaches all need hardware installation or wearable sensors, which incurs additional costs and imposes many restrictions on usage. Therefore, this paper presents a novel device-free activities recognition system based on the advanced wireless technologies. The fine-grained information channel state information (CSI) in the wireless channel is employed as the indicator of human activities. To improve accuracy, both amplitude and phase information of CSI are extracted and shaped into feature vectors for activities recognition. In addition, we discuss the classification accuracy of different features and select the most stable features for feature matrix. Our experimental evaluation in two laboratories of different size demonstrates that the proposed scheme can achieve an average accuracy over 95% and 90% in different scenarios.