• Proceedings of the KOR-BRONCHOESO Conference
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• 1972.03a
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• pp.6-7
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• 1972

The air pollutants can be classified into the irritant gas and the asphixation gas, and the irritant gas is closely related to the otorhinolaryngological diseases. The common irritant gases are nitrogen oxides, sulfur oxides, hydrogen carbon compounds, and the potent and irritating PAN (peroxy acyl nitrate) which is secondarily liberated from photosynthesis. Those gases adhers to the mucous membrane to result in ulceration and secondary infection due to their potent oxidizing power. 1. Sulfur dioxide gas Sulfur dioxide gas has the typical characteristics of the air pollutants. Because of its high solubility it gets easily absorbed in the respiratory tract, when the symptoms and signs by irritation become manifested initially and later the resistance in the respiratory tract brings central about pulmonary edema and respiratory paralysis of origin. Chronic exposure to the gas leads to rhinitis, pharyngitis, laryngitis, and olfactory or gustatory disturbances. 2. Carbon monoxide Toxicity of carbon monoxide is due to its deprivation of the oxygen carrying capacity of the hemoglobin. The degree of the carbon monoxide intoxication varies according to its concentration and the duration of inhalation. It starts with headache, vertigo, nausea, vomiting and tinnitus, which can progress to respiratory difficulty, muscular laxity, syncope, and coma leading to death. 3. Nitrogen dioxide Nitrogen dioxide causes respiratory disturbances by formation of methemoglobin. In acute poisoning, it can cause pulmonary congestion, pulmonary edema, bronchitis, and pneumonia due to its strong irritation on the eyes and the nose. In chronic poisoning, it causes chronic pulmonary fibrosis and pulmonary edema. 4. Ozone It has offending irritating odor, and causes dryness of na sopharyngolaryngeal mucosa, headache and depressed pulmonary function which may eventually lead to pulmonary congestion or edema. 5. Smog The most outstanding incident of the smog occurred in London from December 5 through 8, 1952, because of which the mortality of the respiratory diseases increased fourfold. The smog was thought to be due to the smoke produced by incomplete combustion and its byproduct the sulfur oxides, and the dust was thought to play the secondary role. In new sense, hazardous is the photochemical smog which is produced by combination of light energy and the hydrocarbons and oxidant in the air. The Yonsei University Institute for Environmental :pollution Research launched a project to determine the relationship between the pollution and the medical, ophthalmological and rhinopharyngological disorders. The students (469) of the "S" Technical School in the most heavily polluted area in Pusan (Uham Dong district) were compared with those (345) of "K" High School in the less polluted area. The investigated group had those with subjective symptoms twice as much as the control group, 22.6% (106) in investigated group and 11.3% (39) in the control group. Among those symptomatic students of the investigated group. There were 29 with respiratory symptoms (29%), 22 with eye symptoms (21%), 50 with stuffy nose and rhinorrhea (47%), and 5 with sore thorat (5%), which revealed that more than half the students (52%) had subjective symptoms of the rhinopharyngological aspects. Physical examination revealed that the investigated group had more number of students with signs than those of the control group by 10%, 180 (38.4%) versus 99 (28.8%). Among the preceding 180 students of the investigated group, there were 8 with eye diseases (44%), 1 with respiratory disease (0.6%), 97 with rhinitis (54%), and 74 with pharyngotonsillitis (41%) which means that 95% of them had rharygoical diseases. The preceding data revealed that the otolaryngological diseases are conspicuously outnumbered in the heavily polluted area, and that there must be very close relationship between the air pollution and the otolaryngological diseases, and the anti-pollution measure is urgently needed.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.19-42
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• 2012

Consumer consumption patterns are shifting rapidly as buyers migrate from offline markets to e-commerce routes, such as shopping channels on TV and internet shopping malls. In the offline markets consumers go shopping, see the shopping items, and choose from them. Recently consumers tend towards buying at shopping sites free from time and place. However, as e-commerce markets continue to expand, customers are complaining that it is becoming a bigger hassle to shop online. In the online shopping, shoppers have very limited information on the products. The delivered products can be different from what they have wanted. This case results to purchase cancellation. Because these things happen frequently, they are likely to refer to the consumer reviews and companies should be concerned about consumer's voice. E-commerce is a very important marketing tool for suppliers. It can recommend products to customers and connect them directly with suppliers with just a click of a button. The recommender system is being studied in various ways. Some of the more prominent ones include recommendation based on best-seller and demographics, contents filtering, and collaborative filtering. However, these systems all share two weaknesses : they cannot recommend products to consumers on a personal level, and they cannot recommend products to new consumers with no buying history. To fix these problems, we can use the information which has been collected from the questionnaires about their demographics and preference ratings. But, consumers feel these questionnaires are a burden and are unlikely to provide correct information. This study investigates combining collaborative filtering with the centrality of social network analysis. This centrality measure provides the information to infer the preference of new consumers from the shopping history of existing and previous ones. While the past researches had focused on the existing consumers with similar shopping patterns, this study tried to improve the accuracy of recommendation with all shopping information, which included not only similar shopping patterns but also dissimilar ones. Data used in this study, Movie Lens' data, was made by Group Lens research Project Team at University of Minnesota to recommend movies with a collaborative filtering technique. This data was built from the questionnaires of 943 respondents which gave the information on the preference ratings on 1,684 movies. Total data of 100,000 was organized by time, with initial data of 50,000 being existing customers and the latter 50,000 being new customers. The proposed recommender system consists of three systems : [+] group recommender system, [-] group recommender system, and integrated recommender system. [+] group recommender system looks at customers with similar buying patterns as 'neighbors', whereas [-] group recommender system looks at customers with opposite buying patterns as 'contraries'. Integrated recommender system uses both of the aforementioned recommender systems to recommend movies that both recommender systems pick. The study of three systems allows us to find the most suitable recommender system that will optimize accuracy and customer satisfaction. Our analysis showed that integrated recommender system is the best solution among the three systems studied, followed by [-] group recommended system and [+] group recommender system. This result conforms to the intuition that the accuracy of recommendation can be improved using all the relevant information. We provided contour maps and graphs to easily compare the accuracy of each recommender system. Although we saw improvement on accuracy with the integrated recommender system, we must remember that this research is based on static data with no live customers. In other words, consumers did not see the movies actually recommended from the system. Also, this recommendation system may not work well with products other than movies. Thus, it is important to note that recommendation systems need particular calibration for specific product/customer types.