• Proceedings of the KOR-BRONCHOESO Conference
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• 1972.03a
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• pp.7-8
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• 1972

The effects of noise exposure are of two types: Nonauditory effects and auditory effects. Nonauditory effects of noise exposure are interference with communication by speech, sleeping and emotional behavior. The noise will cause the high blood pressure and rapid pulse, also that decrease the salivation and gastric juice. in experimentaly showed that the Corticoid hormon: Gonatotropic hormone were decrease and Thyrotropic hormoone is increase. Auditory effect of noise exposure. when the normal ear is exposed to noise at noise at hamful intensities (above 90㏈) for sufficiently long periods of time, a temoral depression of hearing results, disappearing after minutes or hours of rest. When the exposure longer or intesity greater is reached the Permanent threshold shift called noise-induced hearing loss. Hearing loss resulting from noise exposure presents legal as well as medical problems. The otologist who examines and evaluates the industrial hearing loss cases must be properly informed, not only concerning the otologic but also about the physical and legal aspects of the problems. The measurement of hearing ability is the most important part of a hearing conservation, both preplacement and periodic follow-up tests of hearing. The ideal hearing conservation program would be able to reduce or eliminate the hazardous noise at its source or by acoustic isolation of noisy working area and two ear protections (plugs and muff type) were developed for personal protection.

• The Korean Journal of Petroleum Geology
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• v.14 no.1
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• pp.1-11
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• 2008

As conventional oil and gas reservoirs become depleted, interests for oil sands has rapidly increased in the last decade. Oil sands are mixture of bitumen, water, and host sediments of sand and clay. Most oil sand is unconsolidated sand that is held together by bitumen. Bitumen has hydrocarbon in situ viscosity of >10,000 centipoises (cP) at reservoir condition and has API gravity between $8-14^{\circ}$. The largest oil sand deposits are in Alberta and Saskatchewan, Canada. The reverves are approximated at 1.7 trillion barrels of initial oil-in-place and 173 billion barrels of remaining established reserves. Alberta has a number of oil sands deposits which are grouped into three oil sand development areas - the Athabasca, Cold Lake, and Peace River, with the largest current bitumen production from Athabasca. Principal oil sands deposits consist of the McMurray Fm and Wabiskaw Mbr in Athabasca area, the Gething and Bluesky formations in Peace River area, and relatively thin multi-reservoir deposits of McMurray, Clearwater, and Grand Rapid formations in Cold Lake area. The reservoir sediments were deposited in the foreland basin (Western Canada Sedimentary Basin) formed by collision between the Pacific and North America plates and the subsequent thrusting movements in the Mesozoic. The deposits are underlain by basement rocks of Paleozoic carbonates with highly variable topography. The oil sands deposits were formed during the Early Cretaceous transgression which occurred along the Cretaceous Interior Seaway in North America. The oil-sands-hosting McMurray and Wabiskaw deposits in the Athabasca area consist of the lower fluvial and the upper estuarine-offshore sediments, reflecting the broad and overall transgression. The deposits are characterized by facies heterogeneity of channelized reservoir sands and non-reservoir muds. Main reservoir bodies of the McMurray Formation are fluvial and estuarine channel-point bar complexes which are interbedded with fine-grained deposits formed in floodplain, tidal flat, and estuarine bay. The Wabiskaw deposits (basal member of the Clearwater Formation) commonly comprise sheet-shaped offshore muds and sands, but occasionally show deep-incision into the McMurray deposits, forming channelized reservoir sand bodies of oil sands. In Canada, bitumen of oil sands deposits is produced by surface mining or in-situ thermal recovery processes. Bitumen sands recovered by surface mining are changed into synthetic crude oil through extraction and upgrading processes. On the other hand, bitumen produced by in-situ thermal recovery is transported to refinery only through bitumen blending process. The in-situ thermal recovery technology is represented by Steam-Assisted Gravity Drainage and Cyclic Steam Stimulation. These technologies are based on steam injection into bitumen sand reservoirs for increase in reservoir in-situ temperature and in bitumen mobility. In oil sands reservoirs, efficiency for steam propagation is controlled mainly by reservoir geology. Accordingly, understanding of geological factors and characteristics of oil sands reservoir deposits is prerequisite for well-designed development planning and effective bitumen production. As significant geological factors and characteristics in oil sands reservoir deposits, this study suggests (1) pay of bitumen sands and connectivity, (2) bitumen content and saturation, (3) geologic structure, (4) distribution of mud baffles and plugs, (5) thickness and lateral continuity of mud interbeds, (6) distribution of water-saturated sands, (7) distribution of gas-saturated sands, (8) direction of lateral accretion of point bar, (9) distribution of diagenetic layers and nodules, and (10) texture and fabric change within reservoir sand body.

• Journal of Bio-Environment Control
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• v.21 no.2
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• pp.95-101
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• 2012

This study was conducted to investigate the effect of climate conditions during cultivation and harvesting on the quality and storability of fresh bulb cabbage (Brassica oleracea L. var. capitata). Plug seedlings of six cabbage cultivars were transplanted to Gangneung-Wonju University high elevation research station in Gangwon province (780 m above sea level, lat. $37.5^{\circ}N$.) and harvested with four different harvest times like August 3 ($1^{st}$), August 13 ($2^{nd}$), August 23 ($3^{rd}$), and September 10 ($4^{th}$), respectively from 50 days after transplanting. Weight loss, Hunter color factors, firmness, and soluble solids content (SSC) of the cabbage bulbs were investigated during storage at $3^{\circ}C$ (85% RH) and $25^{\circ}C$ (60% RH). Decreased bulb weight and poor quality cabbages were apparent at the late transplanting (July 14) and harvest (September 10) respectively. Quality index such as firmness and SSC at August 23 ($3^{rd}$) harvested cabbage was better than August 3 ($1^{st}$) and August 13 ($2^{nd}$) cabbages due to the good weather condition just before harvesting. The cv. 'Speed king' and 'Minix 40' showed good qualities among the cultivars, especially when the bulbs were harvested during sunny day conditions from one week before harvesting. Also SSC was influenced by weather condition before harvesting rather than transplanting date, while firmness was influenced by transplanting and harvest date. However, the differences among the cultivars were not significant. The potential of storage as maintaining the quality was different, depending on weather conditions at harvest time. Generally the storage periods of six cultivars were around 3~5 days and 9~10 days at room and low temperature, respectively. However, the August 3 ($1^{st}$) harvested cabbage lost their marketable quality very fast because of rainy and cloudy weather condition before harvesting and also storability of bulbs was 2 days and 4 days at room temperature and $3^{\circ}C$, respectively. Quality index was also not significant difference among cultivars.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.109-122
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• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.

• Horticultural Science & Technology
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• v.34 no.6
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• pp.886-897
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• 2016

The physical properties of rooting media for the establishment of plugs in a greenhouse are modified according to variations in the greenhouse environment throughout the season. In this study, we established a standard for rooting media for the production of plug seedlings for each growing season (summer, winter and spring fall). Eight types of peatmoss (PM) and 4 types of perlite (PL) commonly used in Korea were collected and blended with the ratio of 7 parts PM to 3 parts PL (v/v) to make 32 different rooting media blends. We determined the total porosity (TP), container capacity (CC), air-filled porosity (AFP), pH, and electrical conductivity (EC) of the 32 media blends, and 6 media blends were selected for seasonal use. We also conducted additional analyses for plant easily available water (EAW), buffering water (BW), cation exchange capacity (CEC), and nutrient contents in the 6 media blends. The TP, CC, and AFP of the 32 media blends ranged from 64.7 to 96.0%, 42.9 to 90.1%, and 1.3 to 27.8%, respectively, indicating that the physical properties were strongly influenced by the type of PM and PL. The pH and EC of the PMs ranged from 2.96 to 3.81 and 0.08 to $0.47dS{\cdot}m^{-1}$, respectively. However, after blending the PM with the PL the pH was raised and the EC was lowered The media blends selected for the summer growing season were Blonde Golden peatmoss (BG) + No. 1 perlite size < 1 mm (PE1) and Latagro 0-10 mm (L1) + No. 2 perlite size 1-2 mm (PE2). These two media blends had 89.8-90.9% of TP, 80.8-81.3% of CC, and 9.0-9.7% of AFP. The media blends selected for the winter growing season were Sfagnumi Turvas (ST) + PE2 and Latagro 20-40 mm (L3) + PE2. These media blends had 79.9-86.7% of TP, 60.4-74.9% of CC, and 11.8-19.6% of AFP. The TP, CC, and AFP of two media blends, BG + No.3 perlite 2-5 mm (PE3) and Orange peatmoss (O) + PE3, selected for the spring and fall growing seasons, respectively, were 85.2-87.3%, 77.9%, and 7.4-9.4%, respectively. The percentage of EAW of the media blends selected for the spring, summer, and winter growing seasons ranged from 24.2-24.9%, 22.0-28.6%, and 18.0-21.8%, respectively, but the percentages of BW were not significantly different among the selected root media blends. The pH, EC, and CEC of the 6 selected media blends ranged from 3.11-3.97, $0.06-0.26dS{\cdot}m^{-1}$, and $97-119meq{\cdot}100g^{-1}$, respectively.