The streaming potential generated by the electrokinetic flow within electric double layer of charged microchannel is applied to determine the zeta potential of hollow-fiber membrane pore by using the general Helmholtz-Smoluchowski equation. The streaming potential is know to provide a useful real-time information on the surface property and the interaction between pore and particles in actual situations and physicochemical conditions. The influence of physicochemical parameters upon the filtration with hollow-fibers has been examined with an in-situ and simultaneously monitoring the streaming potential as well as permeate flux. In particular, the present study examined an experimental method to identify the effect of cake layer which can vary according to the axial position of a hollow-fiber and the progress of membrane fouling by measuring the position-dependent streaming potential. As the latex concentration increases, the permeate flux decreased but the streaming potential increased. The growth of cake layer has been mire developed with increasing latex concentration, however, the effect of surface charges of latexes deposited on the membrane surface leads to increase the streaming potential. With increasing ionic concentration of KCI, both the permeate flux and the streaming potential decrease. The increase of ionic concentration provides a compact cake layer due to the shrinkage of Debye length and the decreased streaming potential results from the weakened ionic flows owing to a thin diffusive double layer.
Journal of Korean Society of Occupational and Environmental Hygiene
/
v.27
no.1
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pp.70-76
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2017
Objectives: This on-site study was performed to evaluate the reduction efficiency of an air cleaner on particulate matters and biological agents in a swine facility. Materials and Methods: Particulate matter was measured using a real-time monitoring recorder and biological agents were sampled with a one-stage impactor and then analyzed based on the microbial culture method. An experimental process for the reduction effect on airborne pollutants through air cleaner operation consisted of three conditions: no treatment, wet scrapper by water spray and wet scrapper by disinfectant spray. Results: Geometric mean levels of particulate matter(TSP, $PM_{10}$, $PM_{2.5}$ and $PM_1$) were presented at $1,608{\mu}g/m^3$, $1,373.8{\mu}g/m^3$, $401.8{\mu}g/m^3$ and $144.5{\mu}g/m^3$ for no treatment; $1,503{\mu}g/m^3$, $1,017{\mu}g/m^3$, $159.4{\mu}g/m^3$ and $69.8{\mu}g/m^3$ for wet scrapper by water spray; and $1,222.17{\mu}g/m^3$, $477.17{\mu}g/m^3$, $33.2{\mu}g/m^3$ and $11.1{\mu}g/m^3$ for wet scrapper by disinfectant spray, respectively. In the case of biological agents, the geometric averaged concentrations of total airborne bacteria and fungi were as follows: $45,371cfu/m^3$ and $13,474cfu/m^3$ for no treatment, $43,286cfu/m^3$ and $8,610cfu/m^3$ for wet scrapper by water spray, and $2,440cfu/m^3$ and 1,867 cfu/ for wet scrapper by disinfectant spray, respectively. Regardless of particulate matter and biological agent, the highest concentrations were found for no treatment, while the lowest concentrations were found with wet scrapper by disinfectant spray. Conclusions: Based on the results obtained from this on-site evaluation, there was a significant reduction effect on particulate matter and biological agents through the application of an air cleaner in this study.
Kim, Nac-Woo;Son, Seung-Chul;Lee, Mun-Seob;Min, Gi-Hyeon;Lee, Byung-Tak
Journal of the Institute of Electronics and Information Engineers
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v.52
no.4
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pp.156-163
/
2015
In this paper, we propose an active water level and distance measurement algorithm using a light beam pattern. On behalf of conventional water level gauge types of pressure, float-well, ultrasonic, radar, and others, recently, extensive research for video analysis based water level measurement methods is gradually increasing as an importance of accurate measurement, monitoring convenience, and much more has been emphasized. By turning a reference light beam pattern on bridge or embankment actively, we suggest a new approach that analyzes and processes the projected light beam pattern image obtained from camera device, measures automatically water level and distance between a camera and a bridge or a levee. As contrasted with conventional methods that passively have to analyze captured video information for recognition of a watermark attached on a bridge or specific marker, we actively use the reference light beam pattern suited to the installed bridge environment. So, our method offers a robust water level measurement. The reasons are as follows. At first, our algorithm is effective against unfavorable visual field, pollution or damage of watermark, and so on, and in the next, this is possible to monitor in real-time the portable-based local situation by day and night. Furthermore, our method is not need additional floodlight. Tests are simulated under indoor environment conditions from distance measurement over 0.4-1.4m and height measurement over 13.5-32.5cm.
The International TOVS(TIROS Operational Vertical Sounders) Process Package(ITPP-VI), which has been installed at Korea Meteorological Administration(KMA), is only for a global usage to need a surface data to generate atmospheric soundings and total ozone amount. If the initial input process in the ITTP-VI is not modified, it takes climatic surface data for producing sounding data and total ozone amount in general. KMA is trying to improve the quality of TOVS total ozone amount using real-time synoptoc observation in various ways instead of climatological data because this retrieved data in the new scheme for total ozone presently used at the KMA may critically provide to analyze the long-term trend of ozone structure over the Korean peninsula. Two cases in this study show that TOVS retrieved total ozone amounts used by synoptic surface observations can delineate more detailed ozone structures rather than those used by climate surface data. The distribution of TOVS retrieved ozone amount fields with the synoptic surface analyzed data(TOVS-GPV) show more in detail relatively than those with the climate data(TOVS-CLIMAT) as expected. In addition, the collocated inter-comparisons of TOVS-GPV with TOVS-CLIMAT, TOMS observations and Dobsometer observations are performed statistically. TOVS-GPV fields with TOMS observations show smaller bias relatively than TOVS-CLIMAT and also reduce the differences.
KIPS Transactions on Software and Data Engineering
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v.8
no.11
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pp.457-464
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2019
The weight of pig is one of the main factors in determining the health and growth state of pigs, their shipment, the breeding environment, and the ration of feed, and thus measuring the pig's weight is an important issue in productivity perspective. In order to estimate the pig's weight by using the number of pig's pixels from images, acquired from a Top-view camera, the posture determining and the head removal from images are necessary to measure the accurate number of pixels. In this research, we propose the fast and accurate method to determine the pig's posture by using a fast image processing technique, find the head location by using a fast deep learning technique, and remove pig's head by using light weighted image processing technique. First, we determine the pig's posture by comparing the length from the center of the pig's body to the outline of the pig in the binary image. Then, we train the location of pig's head, body, and hip in images using YOLO(one of the fast deep learning based object detector), and then we obtain the location of pig's head and remove an outside area of head by using head location. Finally, we find the boundary of head and body by using Convex-hull, and we remove pig's head. In the Experiment result, we confirmed that the pig's posture was determined with an accuracy of 0.98 and a processing speed of 250.00fps, and the pig's head was removed with an accuracy of 0.96 and a processing speed of 48.97fps.
The Changjiang Diluted Water (CDW) spreads over the East China Sea every summer and significantly affects the sea surface salinity changes in the seas around Jeju Island and the southern coast of Korea peninsula. Sometimes its effect extends to the eastern coast of Korea peninsula through the Korea Strait. Specifically, the CDW has a significant impact on marine physics and ecology and causes damage to fisheries and aquaculture. However, due to the limited field surveys, continuous observation of the CDW in the East China Sea is practically difficult. Many studies have been conducted using satellite measurements to monitor CDW distribution in near-real time. In this study, an algorithm for estimating Sea Surface Salinity (SSS) in the East China Sea was developed using the Geostationary Ocean Color Imager (GOCI). The Multilayer Perceptron Neural Network (MPNN) method was employed for developing an algorithm, and Soil Moisture Active Passive (SMAP) SSS data was selected for the output. In the previous study, an algorithm for estimating SSS using GOCI was trained by 2016 observation data. By comparison, the train data period was extended from 2015 to 2020 to improve the algorithm performance. The validation results with the National Institute of Fisheries Science (NIFS) serial oceanographic observation data from 2011 to 2019 show 0.61 of coefficient of determination (R2) and 1.08 psu of Root Mean Square Errors (RMSE). This study was carried out to develop an algorithm for monitoring the surface salinity of the East China Sea using GOCI and is expected to contribute to the development of the algorithm for estimating SSS by using GOCI-II.
Nuclear emergency preparedness and response is an essential part to ensure the safety of nuclear power plant (NPP). Key support technologies of nuclear emergency decision-making usually consist of accident diagnosis, source term estimation, accident consequence assessment, and protective action recommendation. Source term estimation is almost the most difficult part among them. For example, bad communication, incomplete information, as well as complicated accident scenario make it hard to determine the reactor status and estimate the source term timely in the Fukushima accident. Subsequently, it leads to the hard decision on how to take appropriate emergency response actions. Hence, this paper aims to develop a method for rapid source term estimation to support nuclear emergency decision making in pressurized water reactor NPP. The method aims to make our knowledge on NPP provide better support nuclear emergency. Firstly, this paper studies how to build a Bayesian network model for the NPP based on professional knowledge and engineering knowledge. This paper presents a method transforming the PRA model (event trees and fault trees) into a corresponding Bayesian network model. To solve the problem that some physical phenomena which are modeled as pivotal events in level 2 PRA, cannot find sensors associated directly with their occurrence, a weighted assignment approach based on expert assessment is proposed in this paper. Secondly, the monitoring data of NPP are provided to the Bayesian network model, the real-time status of pivotal events and initiating events can be determined based on the junction tree algorithm. Thirdly, since PRA knowledge can link the accident sequences to the possible release categories, the proposed method is capable to find the most likely release category for the candidate accidents scenarios, namely the source term. The probabilities of possible accident sequences and the source term are calculated. Finally, the prototype software is checked against several sets of accident scenario data which are generated by the simulator of AP1000-NPP, including large loss of coolant accident, loss of main feedwater, main steam line break, and steam generator tube rupture. The results show that the proposed method for rapid source term estimation under nuclear emergency decision making is promising.
The imported foods, which are imported and sold domestically, are on the rise every year, and the scale is expected to be larger, including processing the imported raw materials. However, the origin of raw materials is indicated when declaring cargo for finished products of agricultural products, but the standardization of inspection information management system for raw materials is insufficient. In addition, there is a growing concern about the presence of residual pesticides or radioactivity in raw materials or products, and customer want to know production history information when purchasing agrifoods. It manages the hazard analysis of imported agricultural products, but most of them are global issues such as microorganisms, residual pesticides, food additives, and allergy components, etc. Therefore, it is necessary to share among the logistics entities in the entire transportation process the related data. Additionally, to do this, it needs to design an architecture and standardize business model. In this paper, it defines the architecture and the work-flow that occurs between the business process for collecting, processing, and processing information for tracking the status of imported agricultural products by steps, and develops XML message with UBL and the extracted conceptual information model. It will be easy to exchange and share information among the logistics entities through the defined standard model and it will be possible to establish visibility, reliability, safety, and freshness system for transportation of agricultural products requiring real-time management.
Where is a better place to live? In the coming era, this should be more than simply a livable place. It should be an adaptable place that has a flexible system adaptable to any new situation in terms of diversity. Customization and real-time operation are needed in order to realize this technologically. We expect a smart city to have a flexible system that applies technologies of self-monitoring and self-response, thereby being a promising city model towards being a better place to live. Energy demand and supply is a crucial issue concerning our expectations for the flexible system of a smart city because it is indispensable to comfortable living, especially city living. Although it may seem that energy diversification, such as the energy mix of a country, is a matter of overriding concern, the central point is the scale of place to build grids for realizing sustainable urban energy systems. A traditional hard energy path supported by huge centralized energy systems based on fossil and nuclear fuels on a national scale has already faced difficult problems, particularly in terms of energy flexibility/resilience. On the other hand, an alternative soft energy path consisting of small diversified energy systems based on renewable energy sources on a local scale has limitations regarding stability, variability, and supply potential despite the relatively light economic/technological burden that must be assumed to realize it. As another alternative, we can adopt a holonic path incorporating an alternative soft energy path with a traditional hard energy path complimentarily based on load management. This has a high affinity with the flexible system of a smart city. At a system level, the purpose of all of the paths mentioned above is not energy itself but the service it provides. If the expected energy service is fixed, the conclusive factor in choosing a more appropriate system is accessibility to the energy service. Accessibility refers to reliability and affordability; the former encompasses the level of energy self-sufficiency, and the latter encompasses the extent of energy saving. From this point of view, it seems that the small diversified energy systems of a soft energy path have a clear advantage over the huge centralized energy systems of a hard energy path. However, some insuperable limitations still remain, so it is reasonable to consider both energy systems continuing to coexist in a multiplexing energy system employing a holonic path to create and maintain reliable and affordable access to energy services that cover households'/enterprises' basic energy needs. If this is embodied in a smart city concept, this is nothing else but smart energy inclusion. In Japan, following the Fukushima nuclear accident in 2011, a trend towards small diversified energy systems of a soft energy path intensified in order to realize a nuclear-free society. As a result, the Government of Japan proclaimed in its Fifth Strategic Energy Plan that renewable energy must be the main source of power in Japan by 2050. Accordingly, Sony vowed that all the energy it uses would come from renewable sources by 2040. In this situation, it is expected that smart energy inclusion will be achieved by the Japanese version of a smart grid based on the concept of a minimum cost scheme and demand response.
Plato, N.;Bigert, C.;Larsson, B.M.;Alderling, M.;Svartengren, M.;Gustavsson, P.
Safety and Health at Work
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v.10
no.3
/
pp.377-383
/
2019
Objectives: Exposure to fine particles in urban air has been associated with a number of negative health effects. High levels of fine particles have been detected at underground stations in big cities. We investigated the exposure conditions in four occupational groups in the Stockholm underground train system to identify high-exposed groups and study variations in exposure. Methods: $PM_1$ and $PM_{2.5}$ were measured during three full work shifts on 44 underground workers. Fluctuations in exposure were monitored by a real-time particle monitoring instrument, pDR, DataRAM. Qualitative analysis of particle content was performed using inductively coupled plasma mass spectrometry. Nitrogen dioxide was measured using passive monitors. Results: For all underground workers, the geometric mean (GM) of $PM_1$ was $18{\mu}g/m^3$ and of $PM_{2.5}$ was $37{\mu}g/m^3$. The particle exposure was highest for cleaners/platform workers, and the GM of $PM_1$ was $31.6{\mu}g/m^3$ [geometric standard deviation (GSD), 1.6] and of $PM_{2.5}$ was $76.5{\mu}g/m^3$ (GSD, 1.3); the particle exposure was lowest for ticket sellers, and the GM of $PM_1$ was $4.9{\mu}g/m^3$ (GSD, 2.1) and of $PM_{2.5}$ was $9.3{\mu}g/m^3$ (GSD, 1.5). The $PM_1$ and $PM_{2.5}$ levels were five times higher in the underground system than at the street level, and the particles in the underground had high iron content. The train driver's nitrogen dioxide exposure level was $64.1{\mu}g/m^3$ (GSD, 1.5). Conclusions: Cleaners and other platform workers were statistically significantly more exposed to particles than train drivers or ticket sellers. Particle concentrations ($PM_{2.5}$) in the Stockholm underground system were within the same range as in the New York underground system but were much lower than in several older underground systems around the world.
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