• 한국컴퓨터정보학회논문지
• /
• 제20권6호
• /
• pp.107-115
• /
• 2015

벌금형은 형벌체계상 자유형보다 가벼운 형벌로 규정되어 있지만, 자본주의 사회에서는 범죄행위자에게 실질적으로 자유형 못지않은 강력한 제재 수단으로 자리매김하고 있다. 또한 자연인인 개인보다 법인이 저지르는 경제사범, 조세범, 기업범죄에서는 범죄 규모가 클 뿐만 아니라 다른 형사제재 수단이 없는 경우에 사용되는 벌금형을 통한 제재는 형사제재 방법으로서 중요한 가치를 지니고 있다. 그렇지만 우리나라의 벌금형제도는 총액벌금형제도로서 부유한 사람에게는 형벌의 위하적 기능을 수행할 수 없고, 벌금형의 액수에 차이가 많은데도, 벌금형의 실효기간을 똑같게 함으로써 형사재판에서 가장 많이 차지하는 선고형임에도 불구하고, 그 기능을 제대로 수행하고 있다고 할 수 없다. 따라서 현대적 형벌로서 가치를 수행하기 위해서는 총액벌금형제도는 일수벌금형제도로 변경할 필요가 있고, 낮은 벌금형제도는 형법의 보충성 원칙에 따라 범칙금제도로 대체하여 사회적 비난이 낮은 범죄행위자의 개인정보를 보호함과 동시에 형벌의 기능수행을 정상적으로 할 수 있어야 할 것이다. 이와 더불어 벌금형을 선고하는 절차적인 면에서도 피고인의 방어권을 최대한 보장할 수 있는 시스템이 도입되어야 할 필요가 있다. 특히 약식절차에서는 기소와 재판절차가 서면으로만 이루어지면서 피고인의 방어권이 보장되지 못하는 점을 보완하기 위하여 약식명령으로 청구하기 전에 피의자에게 약식절차에 관계되는 필요한 사항을 설명하여 이해시키고, 피고인의 동의를 받을 수 있는 제도의 도입도 필요하다.

• 대기
• /
• 제24권1호
• /
• pp.101-110
• /
• 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.

• 산업경영시스템학회지
• /
• 제46권4호
• /
• pp.32-38
• /
• 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.

• 대기
• /
• 제33권3호
• /
• pp.319-330
• /
• 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.

• 한국산림과학회지
• /
• 제95권2호
• /
• pp.160-167
• /
• 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
• /
• 제9권4호
• /
• pp.79-89
• /
• 2021

본 논문은 사물인터넷 국제 표준 oneM2M을 활용하여 미세먼지(PM10)와 초미세먼지(PM2.5) 측정 플랫폼을 이동식과 고정식으로 설계하였다. 미세먼지 측정 플랫폼은 미세먼지 측정 디바이스, 에이전트, oneM2M 플랫폼, oneM2M IPE, 모니터링 시스템으로 구성하고 설계하였다. 이동식과 고정식의 주요 차이는 이동식은 LTE 연결을 기반으로 사각지대 없이 디바이스와 서비스간에 상호연결을 위해 MQTT 프로토콜을 사용하였고, 고정식은 저전력과 넓은 통신범위를 가진 LoRaWAN 프로토콜을 사용하였다. 미세먼지뿐만 아니라 일상생활과 연관된 온도, 습도, 대기압, 휘발성 유기화합물(VOC), 일산화탄소(CO), 아황산가스(SO2), 이산화질소(NO2), 소음 데이터를 수집하였다. 수집된 센서 값들은 에이전트와 oneM2M IPE를 통해 oneM2M이 제공해주는 공통 API를 활용하여 관리하였고, AE, container 등 4가지 리소스 타입으로 설계하였다. 미세먼지 측정 플랫폼 설계를 통해 동작성, 유연성, 편의성, 안전성, 개방성, 확장성의 6가지 기능을 해석하였다.

• 한국측량학회지
• /
• 제36권5호
• /
• pp.423-432
• /
• 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.

• 한국대기환경학회지
• /
• 제19권2호
• /
• pp.167-177
• /
• 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.

• 한국산업융합학회 논문집
• /
• 제20권4호
• /
• pp.339-343
• /
• 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)
• /
• 제14권6호
• /
• pp.2377-2397
• /
• 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.