In this study, based on an analysis of two DNA barcode markers (cytochrome c oxidase subunit I and cytochrome b genes), we performed species identification and monitored labeling compliance for 50 commercial pufferfish products sold in on-line markets in Korea. Using these barcode sequences as a query for species identification and phylogenetic analysis, we screened the GenBank database. A total of seven pufferfish species (Takifugu chinensis, T. pseudommus, T. xanthopterus, T. alboplumbeus, T. porphyreus, T. vermicularis, and Lagocephalus cheesemanii) were identified and we detected 35 products (70%) that were non-compliant with the corresponding label information. Moreover, the labels on 12 commercial products contained only the general common name (i.e., pufferfish), although not the scientific or Korean names for the 21 edible pufferfish species. Furthermore, the proportion of mislabeled highly processed products (n = 9, 81.8%) was higher than that of simply processed products (n = 26, 66.7%). With respect to the country of origin, the percentage of mislabeled Chinese products (n = 8, 80%) was higher than that of Korean products (n = 26, 66.7%). In addition, the market and dialect names of different pufferfish species were labeled only as Jolbok or Milbok, whereas two non-edible pufferfish species (T. vermicularis and T. pseudommus) were used in six commercial pufferfish products described as JolboK and Gumbok on their labels, which could be attributable to the complex classification system used for pufferfish. These monitoring results highlight the necessity to develop genetic methods that can be used to identify the 21 edible pufferfish species, as well as the need for regulatory monitoring of commercial pufferfish products.

In an automated industry PLC plays a central role to control the manufacturing system. Therefore, fault free operation of PLC controlled manufacturing system is essential in order to maximize a firm's productivity. On the contrary, distributed nature of manufacturing system and growing complexity of the PLC programs presented a challenging task of designing a rapid fault finding system for an uninterrupted process operation. Hence, designing an intelligent monitoring, and diagnosis system is needed for smooth functioning of the operation process. In this paper, we propose a method to continuously acquire a stream of PLC signal data from the normal operational PLC-based manufacturing system and to generate diagnosis model from the observed PLC signal data. Consequently, the generated diagnosis model is used for distinguish the possible abnormalities of manufacturing system. To verify the proposed method, we provided a suitable case study of an assembly line.

Effects of coagulation types on flocculation were investigated by using a photometric dispersion analyzer (PDA) as an on-line monitoring technique in this study. Nakdong River water were used and alum and ferric chloride were used as coagulants. The aim of this study is to compare the coagulation characteristics of alum and ferric chloride by a photometric dispersion analyzer (PDA). Floc growing rates (Rv) in three different water temperatures (4℃, 16℃ and 30℃) and coagulants doses (0.15 mM, 0.20 mM and 0.25 mM as Al, Fe) were measured. The floc growing rate (Rv) by alum was 1.8∼2.8 times higher than that of ferric chloride during rapid mixing period, however, for 0.15 mM∼0.25 mM coagulant doses the floc growing rate (Rv) by ferric chloride was 1.1∼2.3 times higher than that of alum in the slow mixing period at 16℃ water temperature. Reasonable coagulant doses of alum and ferric chloride for turbidity removal were 0.1 mM (as Al) and 0.2 mM (as Fe), respectively, and the removal efficiency of those coagulant doses showed 94% for alum and 97% for ferric chloride. The appropriate coagulant dose of alum and ferric chloride for removing dissolved organic carbon (DOC) showed about 0.3 mM (as Al, Fe) and at this dosage, DOC removal efficiencies were 36% and 44%, and ferric chloride was superior to the alum for removal of the DOC in water.