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Microvibrations may affect the quality and yield of products in precision processes. Therefore, vibration control is essential for minimizing position errors and improving the quality of production. Conventional active vibration isolation systems (AVISs) do not consider the effect of inertia variation, such as the movement of the stage and manipulator, on the system. Variations in inertia are associated with rotational motion, and they require a change in the modeling of an AVIS. Owing to this change, the system may not be optimal and may become unstable because the gain value is close to the critical point of the system. This results in insufficient performance. To overcome these issues, in this study, active vibration isolation was evaluated with the aim of actively controlling an AVIS while considering the effect of inertia variation. The system used in this study consists of an adaptive linear quadratic Gaussian (LQG) controller with six degrees of freedom. The inertia of the entire system changes based on the position of a stage mover. This variation in inertia alters the model of the system. The model is updated using the LQG controller, and the performance of the controller is evaluated. The LQG controller is used to evaluate the followability and transmissibility of the AVIS. The feedback loop is analyzed using Nyquist plots to determine the correlation between inertia variation and robustness. As a result, the phase margin decreases to 40 ° or lower as the rate of inertia variation increases. When the model is updated, the Nyquist's path is included in the unit circle. The correlation between inertia variation and performance is analyzed using Bode plots. The correlation shows a difference of approximately 10 dB depending on whether the model is updated.

This study characterized the water-soluble organic carbon (WSOC) and ionic components of PM2.5 (particles less than 2.5 μm in diameter) from April to June 2016, at Baengnyeong Island The study utilized a particle-into-liquid sampler (PILS) coupled with a total organic carbon (TOC) analyzer and ion chromatography (PILS-TOC-IC). The PM2.5 mean concentration in this study was 23.8±16.7 μg m-3, and the mean of WSOC concentration was 1.6±1.5 μg m-3. Ionic compounds increased by 3.8% in the period in which the air quality standard of PM2.5 (35 μg m-3) was exceeded because the concentration of ionic components increased due to generation by chemical reactions and emissions from a primary source in a nearby urban area. The wind direction and speed were mostly in the northwest and southwest directions and the higher concentration of PM2.5 was also shown in the same directions. In comparison with the previous study, the WSOC/OC ratio was 0.5±0.3 in Baengnyeong Island, which was higher than that at roadside and urban sites and lower than at the background site (Sweden, Aspvreten). It was considered that insoluble OC constituted a major proportion of primary OC that was emitted in urban areas, and the higher WSOC/OC ratios of rural and background sites were affected by inflow. The ratio of nitrate and sulfate in Baengnyeong Island was lower than urban areas in China in other studies, because of emitted aerosols from coal combustion or vehicle emission. The results indicate that Baengnyeong Island was affected by formation of secondary aerosols by chemical reactions and inflow from China as well as domestic emissions. The slope of H+ Aersol/SO₄2- in Baengnyeong Island was 0.079, which was a result of neutralized particle acidity in ambient air. The molar ratio of nitrate and ammonium with sulfate in Baengnyeong Island showed ammoniumrich conditions because ammonium nitrate was increased to homogeneous reaction of ammonia and nitric acid in the gas-phase.

As part of the Megacity Air Pollution Studies (MAPS)-Seoul campaign, three types of research flights were conducted over the Seoul Metropolitan Area (SMA) from May till June 2015 to measure the spatial distribution of a pollution plume near a power plant and petrochemical complex, the vertical profiles of pollutants on the western coast of Korea, and the pollutant distribution in the SMA. The pollution plume (~0–700 m) was highly concentrated and dominated by organic aerosol (OA), which very likely oxidized in the plume, as it showed slightly less oxidation near the source and significantly less oxidation at altitudes above the plume. One vertical profile displayed transitions in concentration and changes in the dominant components, suggesting that the particle sources and/or processing differed above ~1000 m; below 1000 m, where the total mass and OA concentrations were high, sulfate and likely transport sources predominated. The other profile, which was assessed during a separate flight, exhibited sharp increases in the OA number concentration and mean diameter, less oxidized organic content, and higher organic and nitrate concentrations above 1400 m, indicating high-altitude transport and a cleaner boundary layer. Finally, flights investigating the distributions of pollutants in the central, upwind, and downwind SMA regions generally detected high levels of oxidation downwind as well as different aerosol masses between the low and high altitudes. This study highlights the necessity of understanding the complex vertical structures of particle layers, such as those identified in and around the SMA, in order to facilitate the adoption of efficient air quality control strategies and enhance air quality forecasting.

In this work, we address the issues of missing modalities that have arisen from the Visual Question Answer-Difference prediction task and find a novel method to solve the task at hand. We address the missing modality-the ground truth answers-that are not present at test time and use a privileged knowledge distillation scheme to deal with the issue of the missing modality. In order to efficiently do so, we first introduce a model, the "Big" Teacher, that takes the image/question/answer triplet as its input and outperforms the baseline, then use a combination of models to distill knowledge to a target network (student) that only takes the image/question pair as its inputs. We experiment our models on the VizWiz and VQA-V2 Answer Difference datasets and show through extensive experimentation and ablation the performances of our method and a diverse possibility for future research., To appear in CVPR MULA Workshop

The necessity for the aquatic ecological risk assessment for benzophenone-3 (BP-3) is increasing due to its high toxic potential and high detection frequency in freshwater. The initial step in the ecological risk assessment is to determine predicted no-effect concentration (PNEC). This study derived PNEC of BP-3 in freshwater using a species sensitivity distribution (SSD) approach, whilst existing PNECs are derived using assessment factor (AF) approaches. A total of eight chronic toxicity values, obtained by toxicity testing and a literature survey, covering four taxonomic classes (fish, crustaceans, algae, and cyanobacteria) were used for PNEC derivation. Therefore, the quantity and quality of the toxicity data met the minimum requirements for PNEC derivation using an SSD approach. The PNEC derived in this study (73.3 μg/L) was far higher than the environmental concentration detected in freshwater (up to 10.4 μg/L) as well as existing PNECs (0.67~1.8 μg/L), mainly due to the difference in the PNEC derivation methodology (i.e., AF vs. SSD approach). Since the SSD approach is regarded as more reliable than the AF approach, we recommend applying the PNEC value derived in this study for the aquatic ecological risk assessment of BP-3, as the use of the existing PNEC values seems to unnecessarily overestimate the potential ecological risk of BP-3 in freshwater.

The Korea–United States Air Quality (KORUS-AQ) field study was conducted during May–June 2016. The effort was jointly sponsored by the National Institute of Environmental Research of South Korea and the National Aeronautics and Space Administration of the United States. KORUS-AQ offered an unprecedented, multi-perspective view of air quality conditions in South Korea by employing observations from three aircraft, an extensive ground-based network, and three ships along with an array of air quality forecast models. Information gathered during the study is contributing to an improved understanding of the factors controlling air quality in South Korea. The study also provided a valuable test bed for future air quality–observing strategies involving geostationary satellite instruments being launched by both countries to examine air quality throughout the day over Asia and North America. This article presents details on the KORUS-AQ observational assets, study execution, data products, and air quality conditions observed during the study. High-level findings from companion papers in this special issue are also summarized and discussed in relation to the factors controlling fine particle and ozone pollution, current emissions and source apportionment, and expectations for the role of satellite observations in the future. Resulting policy recommendations and advice regarding plans going forward are summarized. These results provide an important update to early feedback previously provided in a Rapid Science Synthesis Report produced for South Korean policy makers in 2017 and form the basis for the Final Science Synthesis Report delivered in 2020.

Large industrial facilities, such as petrochemical complexes, have decisive effects on regional air quality: directly due to their own hazardous volatile organic compounds (VOCs) emissions and indirectly due to their contribution to secondary air pollution. In South Korea, pronounced ozone and particulate matter issues have been reported in industrial areas. In this study, we develop a new top-down VOC emission rate estimation method using in situ airborne formaldehyde (HCHO) observations in the downwind plume of the Daesan Petrochemical Complex (DPC) in South Korea during the 2016 Korea–United States Air Quality (KORUS-AQ) mission. On May 22, we observed a peak HCHO mole fraction of 12 ppb after a transport time of 2.5 h (distance approximately 36 km) under conditions where the HCHO photochemical lifetime was 1.8 h. Box model calculations indicate that this elevated HCHO is mainly due to secondary production (more than 90% after 2 h of plume aging) from various VOC precursors including ethene, propene, and 1,3-butadiene. We estimate a lower limit for yearly DPC VOC emissions of 31 (±8.7) × 103 MT/year for HCHO precursors and 53 (±15) × 103 MT/year for all measured primary VOCs. These estimates are 1.5–2.5 times higher than the latest Korean emission inventories, KORUSv5. This method is beneficial not only by tracking the sources, sinks, and evolution of HCHO but also by validating existing emission inventories.

Virtual libraries have become essential parts of remote learning and working. This paper proposes an event-based framework, called eLIB, for virtual libraries with a focus on the connection between the reality and its virtualization where book placement in the virtual world directly reflects its recent location in the real world. The proposed framework has a presentation layer for users to browse through floors, bookshelves and books. A simple 2D and event-based mechanism uses real images of bookshelves and books instead of creating 3D virtual and augmented reality. This approach can provide adequate virtual user experience without overloading the system and networks compared with typical virtual and augmented reality systems. Each click by users generates an event which is handled by a corresponding Event Handler. The services in eLIB are provided as responses to various events or chains of events. The framework also has a unit to match a book spine image to its content description in the library catalog.

Ketene, a rarely measured reactive VOC, was quantified in the emission plumes from Daesan petrochemical facility in South Korea using airborne PTR-TOF-MS measurements. Ketene mixing ratios as high as ~ 40–50 ppb were observed in the emission plumes. Emission rates of ketene from the facility were estimated using a horizontal advective flux approach and ranged from 84–316 kg h−1. These emission rates were compared to the emission rates of major VOCs such as benzene, toluene, and acetaldehyde. Significant correlations (r2 > 0.7) of ketene with methanol, acetaldehyde, benzene, and toluene were observed for the peak emissions, indicating commonality of emission sources. The calculated average ketene OH reactivity for the emission plumes over Daesan ranged from 3.33–7.75 s−1, indicating the importance of the quantification of ketene to address missing OH reactivity in the polluted environment. The calculated average O3 production potential for ketene ranged from 2.98–6.91 ppb h−1. Our study suggests that ketene has the potential to significantly influence local photochemistry and therefore, further studies focusing on the photooxidation and atmospheric fate of ketene through chamber studies is required to improve our current understanding of VOC OH reactivity and hence, tropospheric O3 production.

We introduce dense relational captioning, a novel image captioning task which aims to generate multiple captions with respect to relational information between objects in a visual scene. Relational captioning provides explicit descriptions for each relationship between object combinations. This framework is advantageous in both diversity and amount of information, leading to a comprehensive image understanding based on relationships, e.g., relational proposal generation. For relational understanding between objects, the part-of-speech (POS; i.e., subject-object-predicate categories) can be a valuable prior information to guide the causal sequence of words in a caption. We enforce our framework to learn not only to generate captions but also to understand the POS of each word. To this end, we propose the multi-task triple-stream network (MTTSNet) which consists of three recurrent units responsible for each POS which is trained by jointly predicting the correct captions and POS for each word. In addition, we found that the performance of MTTSNet can be improved by modulating the object embeddings with an explicit relational module. We demonstrate that our proposed model can generate more diverse and richer captions, via extensive experimental analysis on large scale datasets and several metrics. Then, we present applications of our framework to holistic image captioning, scene graph generation, and retrieval tasks., IEEE TPAMI accepted. Journal extension of our CVPR 2019 paper ( arXiv:1903.05942 ). Source code : https://github.com/Dong-JinKim/DenseRelationalCaptioning

Although much research has been conducted on workaholism, its crossover effects remain uninvestigated, especially in the context of organizations. Based on the job demands-resources (JD-R) model of burnout and the conservation of resources (COR) theory, we established a dual-path structural model to examine the effects of supervisors&rsquo, workaholism on subordinates&rsquo, turnover intention through two types of job demands (perceived workload and interpersonal conflict) as well as subordinates&rsquo, emotional exhaustion. The results revealed that supervisors&rsquo, workaholism is positively related to subordinates&rsquo, emotional exhaustion through increased perceived workload and interpersonal conflict, which result in subordinates&rsquo, turnover intention. This study has made a contribution to the literature by extending the scope of workaholism research from self-perspective to other-perspective. The findings also have practical implications for organizations and their human resources (HR) practitioners.

Even though research on perceiving a calling has been growing, our understanding of its double-edged sword effects and psychological mechanisms remain unclear, especially in terms of work engagement and workaholism. Based on the heavy working investment (HWI) and dualistic model of passion (DMP) theories, we established a dual-path structural model to examine the effects of callings on work engagement and workaholism through two types of passion: harmonious (HP) and obsessive (OP) passions. Our results showed that the association between perceiving a calling and work engagement was partially mediated by HP, while the association between perceiving a calling and workaholism was fully mediated by OP. This study contributes to the literature in that it reveals how perceiving a calling has different effects on work engagement and workaholism through the HWI theoretical lens, as well as the mediating roles of HP and OP, based on the DMP theory. Our findings can be practically applied in organizations and counseling.

The objective of this study was to investigate the behavior of zinc incorporation into newly forming fuel deposits and pre-formed deposits in a simulated pressurized water reactor coolant including 1000 ppm of boron and 2 ppm of lithium at 328 &deg, C. Zinc was incorporated into fuel deposits that were being newly nucleated and grown on nuclear fuel cladding tubes in a zinc-containing coolant. The zinc incorporation resulted in a decrease in the lattice constant of the deposits, which was attributed to the decrease in larger iron content and the corresponding incorporation of smaller zinc in the deposits. However, zinc incorporation was not found, even after the fuel deposits pre-formed before zinc addition were subsequently exposed to the 60 ppb of zinc coolant for 500 h.

Nitrogen oxide (NOx) emissions from the South Korean cement industry are investigated with remote-sensing measurements, surface observations, and in situ aircraft measurements. In the Yeongwol, Danyang, and Jecheon regions of central South Korea, six closely located cement factories produce 31 million tons of cement annually. Their impact on the regional environment has been a public-policy issue, but their pollutants have not been continuously monitored nor have emissions inventories been fully verified. Using a newly developed downscaling technique, remote-sensing analyses show that Ozone Monitoring Instrument (OMI) NO2 column densities over the cement kilns have more than twice the modeled concentrations, indicating that the kilns are one of the most dominant NOx emission point sources in South Korea. Observed NOx emissions are stronger in the spring, suggesting that these sources play an important role in the formation of surface ozone and secondary particulate matter. These emissions also slightly increased in recent years, even while most major South Korean cities posted a declining trend in NOx emissions. Photochemical models (during May to July 2015) demonstrate that emissions from the South Korean cement industry have significant environmental impacts, both on surface ozone (up to approximately 4 ppb) and PM2.5 (up to approximately 2 &micro, g/m3).

A common problem in human-object interaction (HOI) detection task is that numerous HOI classes have only a small number of labeled examples, resulting in training sets with a long-tailed distribution. The lack of positive labels can lead to low classification accuracy for these classes. Towards addressing this issue, we observe that there exist natural correlations and anti-correlations among human-object interactions. In this paper, we model the correlations as action co-occurrence matrices and present techniques to learn these priors and leverage them for more effective training, especially on rare classes. The utility of our approach is demonstrated experimentally, where the performance of our approach exceeds the state-of-the-art methods on both of the two leading HOI detection benchmark datasets, HICO-Det and V-COCO.

In Seoul, South Korea, particulate matters (PMs) significantly decreased for the period 2005–2015 in concert with the implementation of air pollution reduction policies. This study reveals that PM with a diameter smaller than 2.5 μm (PM2.5) has a slower decreasing tendency than PM in the 2.5–10-μm range (PM2.5-10) during summer and that this discrepancy is attributable to the large increase in the summer surface air temperature for the analysis period (0.13°C year–1). During the daytime, especially in the afternoon when the hourly surface air temperature and its increasing rate are high, the difference between the decreasing rates of PM2.5 and PM2.5-10 is pronounced. The slower decrease in PM2.5 compared to PM2.5-10 likely results from the secondary PM2.5 formation being accelerated by the increase in the surface air temperature. Other atmospheric variables that can affect concentrations of PMs, such as insolation, relative humidity, precipitation, wind speed, and sea-level pressure, do not show a meaningful relationship with the discrepancy in the decreasing tendency between the two PMs. Our finding emphasizes the necessity of continuous monitoring and analysis of long-term variability in concentrations of PMs and related meteorological conditions, and the independent establishment of reduction policies for PM2.5 and PM2.5-10 to prepare for anthropogenic climate change and the subsequent air quality change.

The corrosion behaviour of Alloy 690 under four different zinc addition scenarios was investigated in circulating water containing 2 ppm Li and 1000 ppm B at 330 °C. The corrosion rates, release rates, and oxide thicknesses were quantified using gravimetric analyses and oxide compositions. With earlier zinc addition, the corrosion and release rates were accordingly lower and the oxide films were also thinner. This study elaborates on how the radiation source term is suppressed by the zinc addition and the behavior of zinc incorporation into spinel oxides.

To improve the understanding of secondary organic aerosol (SOA) formation from the photo-oxidation of anthropogenic and biogenic precursors at the regional background station on Baengnyeong Island, Korea, gas phase and aerosol chemistries were investigated using the Proton Transfer Reaction Time of Flight Mass Spectrometer (PTR-ToF-MS) and the Aerodyne High Resolution Time of Flight Aerosol Mass Spectrometer (HR-ToF-AMS), respectively. HR-ToF-AMS measured fine particles (PM1 diameter of particle matter less than 1 μm) at a 6-minute time resolution from February to November 2012, while PTR-ToF-MS was deployed during an intensive period from September 21 to 29, 2012. The one-minute time-resolution and high mass resolution (up to 4000 m Δm-1) data from the PTR-ToF-MS provided the basis for calculations of the concentrations of anthropogenic and biogenic volatile organic compounds (BVOCs) including oxygenated VOCs (OVOCs). The dominant BVOCs from the site are isoprene (0.23 ppb), dimethyl sulphide (DMS, 0.20 ppb), and monoterpenes (0.38 ppb). Toluene (0.45 ppb) and benzene (0.32 ppb) accounted for the majority of anthropogenic VOCs (AVOCs). OVOCs including acetone (3.98 ppb), acetaldehyde (2.67 ppb), acetic acid (1.68 ppb), and formic acid (2.24 ppb) were measured. The OVOCs comprise approximately 75% of total measured VOCs, suggesting the occurrence of strong oxidation processes and/or long-range transported at the site. A strong photochemical aging and oxidation of the atmospheric pollutants were also observed in aerosol measured by HR-ToF-AMS, whereby a high f44 : f43 value is shown for organic aerosols (OAs); however, relatively low f44 : f43 values were observed when high concentrations of BVOCs and AVOCs were available, providing evidence of the formation of SOA from VOC precursors at the site. Overall, the results of this study revealed several different SOA formation mechanisms, and new particle formation and particle growth events were identified using the powerful tools scanning mobility particle sizer (SMPS), PTR-ToF-MS, and HR-ToF-AMS.

Our goal in this work is to train an image captioning model that generates more dense and informative captions. We introduce "relational captioning," a novel image captioning task which aims to generate multiple captions with respect to relational information between objects in an image. Relational captioning is a framework that is advantageous in both diversity and amount of information, leading to image understanding based on relationships. Part-of speech (POS, i.e. subject-object-predicate categories) tags can be assigned to every English word. We leverage the POS as a prior to guide the correct sequence of words in a caption. To this end, we propose a multi-task triple-stream network (MTTSNet) which consists of three recurrent units for the respective POS and jointly performs POS prediction and captioning. We demonstrate more diverse and richer representations generated by the proposed model against several baselines and competing methods., Comment: CVPR 2019 (Under review for journal extension). Project page : https://sites.google.com/view/relcap

Constructing an organized dataset comprised of a large number of images and several captions for each image is a laborious task, which requires vast human effort. On the other hand, collecting a large number of images and sentences separately may be immensely easier. In this paper, we develop a novel data-efficient semi-supervised framework for training an image captioning model. We leverage massive unpaired image and caption data by learning to associate them. To this end, our proposed semi-supervised learning method assigns pseudo-labels to unpaired samples via Generative Adversarial Networks to learn the joint distribution of image and caption. To evaluate, we construct scarcely-paired COCO dataset, a modified version of MS COCO caption dataset. The empirical results show the effectiveness of our method compared to several strong baselines, especially when the amount of the paired samples are scarce., Comment: EMNLP 2019. Project page : https://sites.google.com/view/emnlp19scarcecaption

Division of Hematology/Oncology, Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA 02215, USA(Received March 16, 2016: Corrected March 24, 2016: Accepted March 29, 2016)초록: 본 연구에서는 생체 영상 이미징을 위한 다채널 필터 모듈 개발 및 특성 평가 연구를 수행하였다. 필터 모듈은700 nm 및 800 nm 파장대의 근적외선 형광 이미징을 동시에 구현할 수 있도록 제작되었으며, 모듈의 특성 평가를 위해magnification, exposure, gain의 변수에 따른 signal to back ground ratio (SBR)을 통한 대조영상 평가를 진행하였다. 또한 생체 영상 분석을 위해 신장 및 간의 광학적 특성이 동일한 생체 모사 조직인 phantom을 제작하여 두께에 따른 필터모듈의 특성 및 광원의 주입량에 따른 특성 연구를 진행하였다. 제작된 필터 모듈은 magnification, exposure, gain의 변화에도 4이상의 SBR 차이를 보이며, kidney phantom 및 liver phantom의 경우 각각 50 mA, 60 mA의 광원 주입량에서4이상의 SBR 대조 영상을 확인하였다. Abstract: In this study, development of multichannel filter module and characteristic evaluation for bio imaging werestudied. The filter module was fabricated in order to realize near infrared fluorescence imaging of 700 nm and 800 nmwavelength ranges, and contrast imaging analysis for characteristic evaluation of the filter module was studied throughsignal to back ground ratio (SBR), controlled by parameters such as magnification, exposure, gain. Furthermore, phantoms,which are biomimetic tissue with equal optical properties of kidney and liver, were fabricated to study characteristics ofboth filter module depending on thickness and exposure amount of light source for bio imaging analysis. The fabricatedfilter module has more than 4 of SBR difference despite changes of magnification, exposure, gain, and in the case ofthe kidney phantom and the liver phantom, contrast imaging of more than 4 of SBR was confirmed on 50 mA, 60 mAexposure amount of light source respectively.Keywords: Medical image, Fluorescence filter system, Near-infrared fluorescence microscope, Phantom imaging

A multi-level thresholding method for image segmentation is presented. The image is divided into multiple regions based on the grayscale level. The procedure for finding best thresholds is implemented by a genetic algorithm with appropriate coding method. The experiment results show that the proposed method gives a good performance.

Human behavior understanding is arguably one of the most important mid-level components in artificial intelligence. In order to efficiently make use of data, multi-task learning has been studied in diverse computer vision tasks including human behavior understanding. However, multi-task learning relies on task specific datasets and constructing such datasets can be cumbersome. It requires huge amounts of data, labeling efforts, statistical consideration etc. In this paper, we leverage existing single-task datasets for human action classification and captioning data for efficient human behavior learning. Since the data in each dataset has respective heterogeneous annotations, traditional multi-task learning is not effective in this scenario. To this end, we propose a novel alternating directional optimization method to efficiently learn from the heterogeneous data. We demonstrate the effectiveness of our model and show performance improvements on both classification and sentence retrieval tasks in comparison to the models trained on each of the single-task datasets., Comment: 10 pages, 7 figures

To improve understanding of the sources and chemical properties of particulate pollutants on the western side of the Korean Peninsula, an Aerodyne High Resolution Time of Flight Aerosol Mass Spectrometer (HR-ToF-AMS) measured non-refractory fine (PM 1 ) particles from May to November, 2011 at Baengnyeong Island, South Korea. Organic matter and sulfate were generally the most abundant species and exhibited maximum concentrations of 36 μg/m 3 and 39 μg/m 3 , respectively. Nitrate concentrations peaked at 32 μg/m 3 but were typically much lower than sulfate and organic matter concentrations. May, September, October, and November featured the highest monthly average concentrations, with lower concentrations typically observed from June through August. Potential source contribution function (PSCF) analysis and individual case studies revealed that transport from eastern China, an area with high SO 2 emissions, was associated with high particulate sulfate concentrations at the measurement site. Observed sulfate aerosol sometimes was fully neutralized by ammonium but often was acidic; the average ammonium to sulfate molar ratio was 1.49. Measured species size distributions revealed a range of sulfate particle size distributions with modes between 100 and 600 nm. Organic aerosol source regions were widespread, including contributions from eastern China and South Korea. Positive matrix factorization (PMF) analysis indicated three “factors,” or types of organic aerosol, comprising one primary, hydrocarbon-like organic aerosol (HOA) and two oxidized organic aerosol (OOA) components, including a more oxidized (MO-OOA) and a less oxidized (LO-OOA) oxidized organic aerosol. On average, HOA and OOA contributed 21% and 79% of the organic mass (OM), respectively, with the MO-OOA fraction nearly three times as abundant as the LO-OOA fraction. Biomass burning contributions to observed OM were low during the late spring/early summer agricultural burning season in eastern China, since airflow into eastern China during the Asian Monsoon generally prevents transport of emissions eastward to the Korean Peninsula. Concentrations of the m/z 60 AMS biomass burning marker were more abundant in autumn, when transport patterns appeared to bring some smoke from fires in northern Asia to the island.

To establish National Reference Method (NRM) for , operational performance of 5 different commercial gravimetric-based measuring instruments was assessed at Bulkwang monitoring station from January 23, 2014 to February 28, 2014. First, physical properties, design, and functional performance of the instruments were assessed. Evaluation was carried out to determine whether operating method for the instruments and levels of QA/QC activities meet the data quality objectives (DQOs). To verify whether DQOs were satisfied, reproducibility of QA/QC procedures, accuracy, relative sensitivity, limit of detection, margin of error, and coefficient of determination of the instruments were also evaluated. Results of flow rate measurement of 15 candidate instruments indicated that all the instruments met performance criteria with accuracy deviation of 4.0% and reproducibility of 0.6%. Comparison of final mass concentrations showed that the coefficient of determination () values were greater than or equal to 0.9995, and concentration gradient ranged from 0.97 to 1.03. All the instruments satisfied criteria for NRM with the estimated precision of 1.47~2.60%, accuracy of -1.90~3.00%, and absolute accuracy of 1.02~3.12%. This study found that one particular type of measuring instrument was proved to be excellent, with overall evaluation criteria satisfied.

In the past several decades, biofuels have emerged as candidates to help mitigate the issues of global warming, fossil fuel depletion and, in some cases, atmospheric pollution. To date, the only biofuels that have achieved any significant penetration in the global transportation sector are ethanol and biodiesel. The global consumption of biodiesel was rapidly increased from 2005. The goal of this study was to examine the chemical composition on particulate pollutant emissions from a diesel engine operating on several different biodiesels. Tests were performed on non-road diesel engine. Experiments were performed on 5 different fuel blends at 2 different engine loading conditions (50% and 75%). 5 different fuel blends were ultra-low sulfur diesel (ULSD, 100%), soy biodiesel (Blend 20% and Blend 100%) and canola biodiesel (Blend 20% and Blend 100%). The chemical properties of particulate pollutants were characterized using an Aerodyne High Resolution Time of Flight Aerosol Mass Spectrometer (HR-ToF-AMS). Organic matter and nitrate were generally the most abundant aerosol components and exhibited maximum concentration of 1207 μg/m³ and 30 μg/m³, respectively. On average, the oxidized fragment families (C x H y O₁+, and C x H y O z +) account for ~13% of the three family sum, while ~87% comes from the C x H y + family. The two peaks of C₂H₃O₂ (m/z 59.01) and C₃H 7 O (m/z 59.04) located at approximately m/z 59 could be used to identify atmospheric particulate matter directly to biodiesel exhaust, as distinguished from that created by petroleum diesel in the AMS data.

Compact size and low cost hermetic sealed 100 Gb/s (25 Gb/s × 4 channels) ROSA using AlN substrate and SiOB cover without expensive ceramic package and mechanical machining components have been designed and fabricated. The fabricated ROSA satisfies IEEE 100GBASE Ethernet LR4 specifications.

One of the most hazardous driving scenario is the overtaking of a slower vehicle, indeed, in this case the front vehicle (being overtaken) can occlude an important part of the field of view of the rear vehicle's driver. This lack of visibility is the most probable cause of accidents in this context. Recent research works tend to prove that augmented reality applied to assisted driving can significantly reduce the risk of accidents. In this paper, we present a real-time marker-less system to see through cars. For this purpose, two cars are equipped with cameras and an appropriate wireless communication system. The stereo vision system mounted on the front car allows to create a sparse 3D map of the environment where the rear car can be localized. Using this inter-car pose estimation, a synthetic image is generated to overcome the occlusion and to create a seamless see-through effect which preserves the structure of the scene.

We address the problem of composing a story out of multiple short video clips taken by a person during an activity or experience. Inspired by plot analysis of written stories, our method generates a sequence of video clips ordered in such a way that it reflects plot dynamics and content coherency. That is, given a set of multiple video clips, our method composes a video which we call a video-story. We define metrics on scene dynamics and coherency by dense optical flow features and a patch matching algorithm. Using these metrics, we define an objective function for the video-story. To efficiently search for the best video-story, we introduce a novel Branch-and-Bound algorithm which guarantees the global optimum. We collect the dataset consisting of 23 video sets from the web, resulting in a total of 236 individual video clips. With the acquired dataset, we perform extensive user studies involving 30 human subjects by which the effectiveness of our approach is quantitatively and qualitatively verified.

Overtaking accidents typically occur when the rear car intends to overtake the front car with limited visibility. This lack of visual information is often attributed to the occlusion caused by the front vehicle. Indeed, in many situations the front car hides the presence of obstacles, such as pedestrians or other cars. Nowadays, the generalization of digital camera embedded automotives represents a great potential to reduce the number of these deadly accidents. Thus, we propose a novel collaborative cars method which allows a driver to literally see through the front vehicle to assist in overtaking manoeuvres. In the studied scenario, both cars are equipped with cameras (stereo and monocular cameras for the front and the rear cars, respectively) and share data through an appropriated wireless communication system. Our method generates a seamless transparency effect from the rear car viewpoint using tri-focal tensor image synthesis where the poses of the cameras are estimated using a marker-based pose estimation. In this article, we present an efficient framework designed to reduce the quantity of information to be transferred between the vehicles and to achieve real-time performances (15 fps). Furthermore, our system is assessed through multiple experiments in controlled and real conditions.

The purpose of this study is to understand distribution of ozone concentration in the south coastal region of Korea by evaluating ozone spatial distribution in the upper air using aircraft. Sampling was carried out from May to August in 2009. The average concentration of ozone in the upper air was ranged from 32.3~90.8 ppb with its maximum concentration of 132 ppb. When it comes to the spatial distribution of ozone, ambient concentration was high in the air, 1,000 m and 500 m above the southern sea near the Gwangyang Bay area and emission sources, respectively. Daily mean concentration of NOy was 6.7~24.2 ppb and that of CO was 0.152~0.487 ppm. In addition, the concentration was appeared to be relatively high in the upper air of industrial regions and the southern seas. Meanwhile, the concentration of both and CO was high in the upper air of the emission sources regardless of latitude. As for PAN, its daily mean concentration ranged between 0.1 and 0.6 ppb with overall mean concentration of 0.2 ppb. The average concentration of VOCs was 48 ppb, and the concentration of toluene and m,p-Xylene were higher than other components.

This study aims to identify the impacts of air quality in the Korean Peninsula according to the China's environmental policies in preparation of the Beijing 2008 Olympic Games. The measurement of emission variations in China, aircraft measurement, and modelling were carried out. The reduction measures in Beijing, China and its emission changes resulted in in decrease out of the total emissions within the Beijing region, whereas when it comes to the whole nation of China, the reduction rate was about . Comparing the concentration of the air pollutants in Seoul and Ganghwa in August 2008 during around the period of Beijing Olympic Games with one in showed that the concentrations in the past was above 5ppb, while the concentration in the 2008 olympic period was 4ppb and below. The NOx at the Seokmori site in Ganghwa tended to be lower in concentration in 2008 than in between . As for and , the concentration tended to be rather low since August 11. The air current track that showed during the period of aircraft measurement presented to be flowed into Korea through the Northeast part of China and the coast of Bohai Bay, while the concentrations of . NOx, and over the west sea on August 20 and 24 were 0.54 (0.28ppb), 0.86 (1.84ppb), and 54.0 (41.5ppb) respectively, similar or lower than the ones measured in the past in the similar current patterns. The modelling result showed similar patterns to the data of aircraft measurement, in particular in . Overall, the reduction measures in Beijing, China affected directly and indirectly the air quality in the Korean peninsular, but the impact was not significant as it was momentary and limited to the intended area.