• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.177-192
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• 2012

This is a study of match-making systems that considers the mutual satisfaction of matching partners. Recently, recommendation systems have been applied to people recommendation, such as recommending new friends, employees, or dating partners. One of the prominent domain areas is match-making systems that recommend suitable dating partners to customers. A match-making system, however, is different from a product recommender system. First, a match-making system needs to satisfy the recommended partners as well as the customer, whereas a product recommender system only needs to satisfy the customer. Second, match-making systems need to include as many participants in a matching pool as possible for their recommendation results, even with unpopular customers. In other words, recommendations should not be focused only on a limited number of popular people; unpopular people should also be listed on someone else's matching results. In product recommender systems, it is acceptable to recommend the same popular items to many customers, since these items can easily be additionally supplied. However, in match-making systems, there are only a few popular people, and they may become overburdened with too many recommendations. Also, a successful match could cause a customer to drop out of the matching pool. Thus, match-making systems should provide recommendation services equally to all customers without favoring popular customers. The suggested match-making system, called Mutually Beneficial Matching (MBM), considers the reciprocal satisfaction of both the customer and the matched partner and also considers the number of customers who are excluded in the matching. A brief outline of the MBM method is as follows: First, it collects a customer's profile information, his/her preferable dating partner's profile information and the weights that he/she considers important when selecting dating partners. Then, it calculates the preference score of a customer to certain potential dating partners on the basis of the difference between them. The preference score of a certain partner to a customer is also calculated in this way. After that, the mutual preference score is produced by the two preference values calculated in the previous step using the proposed formula in this study. The proposed formula reflects the symmetry of preferences as well as their quantities. Finally, the MBM method recommends the top N partners having high mutual preference scores to a customer. The prototype of the suggested MBM system is implemented by JAVA and applied to an artificial dataset that is based on real survey results from major match-making companies in Korea. The results of the MBM method are compared with those of the other two conventional methods: Preference-Based Matching (PBM), which only considers a customer's preferences, and Arithmetic Mean-Based Matching (AMM), which considers the preferences of both the customer and the partner (although it does not reflect their symmetry in the matching results). We perform the comparisons in terms of criteria such as average preference of the matching partners, average symmetry, and the number of people who are excluded from the matching results by changing the number of recommendations to 5, 10, 15, 20, and 25. The results show that in many cases, the suggested MBM method produces average preferences and symmetries that are significantly higher than those of the PBM and AMM methods. Moreover, in every case, MBM produces a smaller pool of excluded people than those of the PBM method.

• Korean Journal of Soil Science and Fertilizer
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• v.32 no.4
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• pp.383-397
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• 1999

For sites to be investigated, the results of such an investigation can be used in determining foals for cleanup, quantifying risks, determining acceptable and unacceptable risk, and developing cleanup plans t hat do not cause unnecessary delays in the redevelopment and reuse of the property. To do this, it is essential that an appropriately detailed study of the site be performed to identify the cause, nature, and extent of contamination and the possible threats to the environment or to any people living or working nearby through the analysis of samples of soil and soil gas, groundwater, surface water, and sediment. The migration pathways of contaminants also are examined during this phase. Key aspects of cost-effective site assessment to help standardize and accelerate the evaluation of contaminated soils at sites are to provide a simple step-by-step methodology for environmental science/engineering professionals to calculate risk-based, site-specific soil levels for contaminants in soil. Its use may significantly reduce the time it takes to complete soil investigations and cleanup actions at some sites, as well as improve the consistency of these actions across the nation. To achieve the effective site assessment, it requires the criteria for choosing the type of standard and setting the magnitude of the standard come from different sources, depending on many factors including the nature of the contamination. A general scheme for site-specific assessment consists of sequential Phase I, II, and III, which is defined by workplan and soil screening levels. Phase I are conducted to identify and confirm a site's recognized environmental conditions resulting from past actions. If a Phase 1 identifies potential hazardous substances, a Phase II is usually conducted to confirm the absence, or presence and extent, of contamination. Phase II involve the collection and analysis of samples. And Phase III is to remediate the contaminated soils determined by Phase I and Phase II. However, important factors in determining whether a assessment standard is site-specific and suitable are (1) the spatial extent of the sampling and the size of the sample area; (2) the number of samples taken: (3) the strategy of taking samples: and (4) the way the data are analyzed. Although selected methods are recommended, application of quantitative methods is directed by users having prior training or experience for the dynamic site investigation process.

• Journal of Food Hygiene and Safety
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• v.38 no.2
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• pp.37-45
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• 2023

The surge in food delivery systems during the coronavirus 2019 pandemic necessitated this study of heavy metal migration from food contact materials (FCMs). A total of 104 samples of FCMs, comprising 51 polypropylene (PP), 21 polyethylene (PE), and 32 polystyrene (PS) samples of six different types of FCMs (containers, covers, table utensils, cups, pouches, and wrappers) used for food delivery distributed in Korea, were collected and investigated for migration of three heavy metals (Pb, Cd, and As) using inductively coupled plasma-mass spectrometry (ICP-MS) to determine whether they complied with Korea's Standards and Specifications for Utensils, Containers, and Packages. Acetic acid (4%, v/v) was used as the food simulant, and tests were performed at 100℃ (in harsh conditions) for 30 min. Linearity of Pb, Cd, and As showed acceptable results with a coefficient of determination (R²) value of 0.9999. Limit of detection (LOD) and limit of quantification (LOQ) of Pb, Cd, and As were 0.001, 0.001, and 0.001 ㎍/L and 0.002, 0.003, and 0.003 ㎍/L, respectively. Accuracy and precision results complied with the criteria presented in the European Commission Joint Research Centre guidelines. The average concentration of Pb, Cd, and As migration detected in a total of 104 samples was 0.009-0.260 ㎍/L, which was very low compared with the migration specification set in the Standards and Specifications for Utensils, Containers, and Packages. The maximum level of Pb corresponded to 0.23% of the migration limit. There were no samples exceeding the limit. Thus, this study confirmed that the heavy metal contents of FCMs used for delivery food distributed in Korea were safely managed. The data from this study represent an invaluable source for science-based safety management of hazardous heavy metals migrating from FCMs used in the food delivery industry.