• IE interfaces
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• v.19 no.1
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• pp.43-52
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• 2006

In order to make best use of NC machine tools with minimal labor costs, they need to be in operation 24 hours a day without being attended by human operators except for setup and tool changes. Thus, unattended machining is becoming a dream of every modern machine shop. However, without a proper mechanism for real-time monitoring of the machining processes, unattended machine could lead to a disaster. Investigated in this paper are ways to using PC camera as a real-time monitoring system for unattended NC milling operations. This study defined five machining states READY, NORMAL MACHINING, ABNORMAL MACHINING, COLLISION and END-OF-MACHINING and modeled them with DEVS (discrete event system) formalism. An image change detection algorithm has been developed to detect the table movements and a flame and smoke detection algorithm to detect unstable cutting process. Spindle on/off and cutting status could be successfully detected from the sound signals. Initial experimentation shows that the PC camera could be used as a reliable monitoring system for unattended NC machining.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.5
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• pp.783-790
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• 2022

The development of SNS and video platforms provided an opportunity to explode the activation of content production and consumption. However, in the legacy system, due to the host-based location-oriented data transmission, there are inherent limitations in efficient operation and management. As an alternative to this, a Contents Centric Network (CCN) was studied. In this paper, when intermediate nodes located between the information provider and the information requester between the real-time streaming services in the CCN environment move or restrict their use, failure through monitoring of wireless reception strength to solve problems like disconnection of transmission quality at the information consumer. We propose a stable intermediate node management mechanism through active response before occurrence.

• Journal of Dairy Science and Biotechnology
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• v.39 no.2
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• pp.51-62
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• 2021

Escherichia coli are the predominant facultative bacteria found in the gastrointestinal tract of animals and humans. Some strains of E. coli that acquire virulence factors and cause foodborne and waterborne diseases in humans are called pathogenic E. coli and can be divided into five pathotypes according to the virulence mechanism: EAEC, EHEC, EIEC, EPEC, and ETEC. Although selective media have been developed to detect E. coli, distinguishing pathogenic strains from non-pathogenic ones is difficult because of their similar biochemical properties. Therefore, it is very important to find a new and effective diagnostic method to identify pathogenic E. coli. With recent advances in molecular biology and whole genome sequencing, the use of polymerase chain reaction (PCR) is increasing rapidly. In this review paper, we provide an overview of pathogenic E. coli and present a review on PCR detection methods that can be used to diagnose pathogenic E. coli. In addition, the possibility of real-time PCR incorporating IAC is introduced. Consequently, this review paper will contribute to solving the current challenges related to the detection of pathogenic E. coli.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.3868-3888
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• 2022

A widely used social networking service like Twitter has the ability to disseminate information to large groups of people even during a pandemic. At the same time, it is a convenient medium to share irrelevant and unverified information online and poses a potential threat to society. In this research, conventional machine learning algorithms are analyzed to classify the data as either non-rumor data or rumor data. Machine learning techniques have limited tuning capability and make decisions based on their learning. To tackle this problem the authors propose a deep learning-based Rumor Detection Neural Network model to predict the rumor tweet in real-world events. This model comprises three layers, AttCNN layer is used to extract local and position invariant features from the data, AttBi-LSTM layer to extract important semantic or contextual information and HPOOL to combine the down sampling patches of the input feature maps from the average and maximum pooling layers. A dataset from Kaggle and ground dataset #gaja are used to train the proposed Rumor Detection Neural Network to determine the veracity of the rumor. The experimental results of the RDNN Classifier demonstrate an accuracy of 93.24% and 95.41% in identifying rumor tweets in real-time events.

• BMB Reports
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• v.43 no.7
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• pp.480-484
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• 2010

The Bombyx mori Microarray Database (BmMDB; http://silkworm.swu.edu.cn/microarray) provides information for tissue-specific gene expression by using the whole-genome oligonucleotide microarray in the silkworm. We analyzed the tissue-specific expression patterns in the silk gland, fat body, and midgut five days of fifth instar larvae during the development of B. mori. To verify the tissue-specific expression, analysis was conducted using quantitative Real-time RT-PCR and the highly expressed endogenous Actin RNA as an intrinsic reference. Finally, we confirmed five genes, (sw15872, sw00692, sw20990, sw05300,and sw2250), out of 18 candidates expressed in two different tissues, which was consistent with the data published by Dr. Xiang's group, thereby supporting the BmMDB. Further studies for promoter regions of candidate genes can be applied in creating transgenic silkworms as biomedical insects for use in producing biomaterials, and to serve as well-characterized models for understanding the mechanism for the genetic regulation of tissue-specific development.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.18
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• pp.8467-8471
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• 2016

Background: One of the major mechanisms for drug resistance is associated with altered anticancer drug transport, mediated by the human-adenosine triphosphate binding cassette (ABC) transporter superfamily proteins. The overexpression of adenosine triphosphate binding cassette, sub-family B, member 1 (ABCB1) by multidrug-resistant cancer cells is a serious impediment to chemotherapy. In our study we have studied the possibility that structural single-nucleotide polymorphisms (SNP) are the mechanism of ABCB1 overexpression. Materials and Methods: A total of 101 gastric cancer multidrug resistant cases and 100 controls were genotyped with sequence-specific primed PCR (SSP-PCR). Gene expression was evaluated for 70 multidrug resistant cases and 54 controls by real time PCR. The correlation between the two groups was based on secondary structures of RNA predicted by bioinformatics tool. Results: The results of genotyping showed that among 3 studied SNPs, rs28381943 and rs2032586 had significant differences between patient and control groups but there were no differences in the two groups for C3435T. The results of real time PCR showed over-expression of ABCB1 when we compared our data with each of the genotypes in average mode. Prediction of secondary structures in the existence of 2 related SNPs (rs28381943 and rs2032586) showed that the amount of ${\Delta}G$ for original mRNA is higher than the amount of ${\Delta}G$ for the two mentioned SNPs. Conclusions: We have observed that 2 of our studied SNPs (rs283821943 and rs2032586) may elevate the expression of ABCB1 gene, through increase in mRNA stability, while this was not the case for C3435T.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.05a
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• pp.205-208
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• 2011

In recent years, the user interest has increased for DDS (Data Distribution Service) which is a data centric middleware based on publish-subscribe communication as the demands for real-time data exchange in distributed systems have been growing rapidly. To reflect these needs, many vendors and research groups provide their DDS middleware. However, there has been a problem with interoperability between DDS middlewares because of a lack of common communication rules such as the message exchange and the discovery manner. For this reason, OMG defines RTPS (Real-Time Publish-Subscribe) specification which is the standard network protocol used to exchange data between different implementations of DDS. In this paper, we analyze and design the SDP (Simple Discovery Protocol) of RTPS which enable DDS middleware to provide interoperable discovery mechanism.

• Asia pacific journal of information systems
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• v.12 no.4
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• pp.193-213
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• 2002

The sales activity of most of small manufacturing companies is based on orders of buyers. The process of promotion, negotiation, receipt and selection of orders of the manufacturers is closely coupled with the load status of the production lines. The decision on whether to accept an order or not, or the selection of optimal order set among excessive orders is entirely dependent on the schedule of production lines. However, in the real world, since the production scheduling activity is mainly performed by human experts, most of small manufacturers are suffer from being unable to meet due dates, lack of rapid decision on the acceptance of new order. Recently, Internet based Electronic Commerce is recognized as one of the alternatives for strengthening sales power of small and medium companies. However, small and medium manufacturers can't adjust properly to the new environment because they are in short of money, personnel, and technology. To cope with this problem, this paper deals with development of part sales agent coupled with virtual manufacturing in Internet environment that consist of selection agent, advertisement agent, selection agent, negotiation agent, and virtual manufacturing system. This paper develops a time-bounded negotiation mechanism for small and medium manufacturers in agent-based automated negotiation between customers and negotiation agents. Furthermore, to select optimal order set maximized profit, we first formulate the order selection problem with mixed integer programming, but the computation time of IP is not acceptable for real world scale problem. To overcome this problem and dynamic nature of virtual manufacturing, we suggest a genetic algorithm approach, which shows a reasonable computation time for real world case and good incremental problem solving capability.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.1
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• pp.35-42
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• 2013

This paper shows the positivistic approach for analyzing the effect of ICT on the reduction of greenhouse gas (GHG) emission. The real-time navigation was selected for the ICT based service in this research, and the CO2 reduction ratios of the optimized routes in the navigation were compared with the reduction ratios of the shortest routes in existing navigations. The results of experiments showed the driving based on the optimized routes has more reduction effects than the driving on the basis of the shortest routes. Also, new evaluation method for GHG emission was suggested by the quantification and monitoring approaches on the basis of the Clean Development Mechanism (CDM) in this paper. The results of this paper can be used as a preliminary research for the effect of ICT on the reduction of GHG emission. The evaluation method which suggested in this paper will be suggested to CDM as the new standard for the reduction of GHG emission in the transportation field as well.

• Journal of Chest Surgery
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• v.44 no.2
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• pp.123-130
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• 2011

Background: The aim of the present study was to identify chromosomal loci that contribute to the pathogenesis of aortic dissection (AD) in a Korean population using array comparative genomic hybridization (CGH) and to confirm the results using real-time polymerase chain reaction (PCR). Materials and Methods: Eighteen patients with ADs were enrolled in this study. Genomic DNA was extracted from individual blood samples, and array CGH analyses were performed. Four corresponding genes with obvious genomic changes were analyzed using real-time PCR in order to assess the level of genomic imbalance identified by array CGH. Results: Genomic gains were most frequently detected at 8q24.3 (56%), followed by regions 7q35, 11q12.2, and 15q25.2 (50%). Genomic losses were most frequently observed at 4q35.2 (56%). Real-time PCR confirmed the results of the array CGH studies of the COL6A2, DGCR14, PCSK6, and SDHA genes. Conclusion: This is the first study to identify candidate regions by array CGH in patients with ADs. The identification of genes that may predispose an individual to AD may lead to a better understanding of the mechanism of AD formation. Further multicenter studies comparing cohorts of patients of different ethnicities are warranted.