• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.680-683
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• 1997

Fieldbus system should be designed by considering the number of sensors/actors(actuators+ controllers) and their sampling times. But the number of sensors/actors and which are connected to the network bus can be varied by addition and/or fault of the field devices. That variation decreases the efficiency of system which is off-line designed optimally. This paper proposes an algorithm that ensures transmission of cyclic data even though there is the number change in the field devices. We assign the different weight values to cyclic data and acyclic data. By simulation and experiment, the cyclic and acyclic data are processed via the proposed network, and the results are compared with those of the Profibus system. It is shown that the proposed algorithm is more robust with the uncertainties of the field devices of the control system.

• Kyungpook Mathematical Journal
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• v.57 no.2
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• pp.211-222
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• 2017

In this paper, we consider three inverse eigenvalue problems for a special type of acyclic matrices. The acyclic matrices considered in this paper are described by a graph called a broom on n + m vertices, which is obtained by joining m pendant edges to one of the terminal vertices of a path on n vertices. The problems require the reconstruction of such a matrix from given partial eigen data. The eigen data for the first problem consists of the largest eigenvalue of each of the leading principal submatrices of the required matrix, while for the second problem it consists of an eigenvalue of each of its trailing principal submatrices. The third problem has an eigenvalue and a corresponding eigenvector of the required matrix as the eigen data. The method of solution involves the use of recurrence relations among the leading/trailing principal minors of ${\lambda}I-A$, where A is the required matrix. We derive the necessary and sufficient conditions for the solutions of these problems. The constructive nature of the proofs also provides the algorithms for computing the required entries of the matrix. We also provide some numerical examples to show the applicability of our results.

• Journal of Korea Society of Industrial Information Systems
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• v.9 no.2
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• pp.9-16
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• 2004

Recently, lattice conditional independence models(LCIMs) have been introduced for the analysis of non-monotone missing data patterns and of non-nested dependent regression models. This approach has been successfully applied to solve various problems in data pattern analysis, however, it suffers from computational burden to search LCIMs. In order to cope with this drawback, we propose a new scheme for finding LCIMs based on the essential graph. Also, we show that the class of LCIMs coincides with the class of all transitive acyclic directed graph(TADG) models which are Markov equivalent to a specific acyclic directed graph(ADG) models.

• Journal of Information Processing Systems
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• v.16 no.1
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• pp.201-209
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• 2020

The graph data structure is popular because it can intuitively represent real-world knowledge. Graph databases have attracted attention in academia and industry because they can be used to maintain graph data and allow users to mine knowledge. Mining reachability relationships between two nodes in a graph, termed reachability query processing, is an important functionality of graph databases. Online traversals, such as the breadth-first and depth-first search, are inefficient in processing reachability queries when dealing with large-scale graphs. Labeling schemes have been proposed to overcome these disadvantages. The state-of-the-art is the 2-hop labeling scheme: each node has in and out labels containing reachable node IDs as integers. Unfortunately, existing 2-hop labeling schemes generate huge 2-hop label sizes because they only consider local features, such as degrees. In this paper, we propose a more efficient 2-hop label size reduction approach. We consider the topological sort index, which is a global feature. A linear combination is suggested for utilizing both local and global features. We conduct experiments over real-world and synthetic directed acyclic graph datasets and show that the proposed approach generates smaller labels than existing approaches.

• The Korean Journal of Applied Statistics
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• v.33 no.3
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• pp.309-320
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• 2020

Bayesian networks, also known as directed acyclic graphs (DAG), are used in many areas of medicine, meteorology, and genetics because relationships between variables can be modeled with graphs and probabilities. In particular, Bayesian network classifiers, which are used to predict discrete data, have recently become a new method of data mining. Bayesian networks can be grouped into different models that depend on structured learning methods. In this study, Bayesian network models are learned with various properties of structure learning. The models are compared to the simplest method, the naïve Bayes model. Classification results are compared by applying learned models to various real data. This study also compares the relationships between variables in the data through graphs that appear in each model.

• ETRI Journal
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• v.39 no.4
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• pp.592-604
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• 2017

Intrusion detection is very important for network situation awareness. While a few methods have been proposed to detect network intrusion, they cannot directly and effectively utilize semi-quantitative information consisting of expert knowledge and quantitative data. Hence, this paper proposes a new detection model based on a directed acyclic graph (DAG) and a belief rule base (BRB). In the proposed model, called DAG-BRB, the DAG is employed to construct a multi-layered BRB model that can avoid explosion of combinations of rule number because of a large number of types of intrusion. To obtain the optimal parameters of the DAG-BRB model, an improved constraint covariance matrix adaption evolution strategy (CMA-ES) is developed that can effectively solve the constraint problem in the BRB. A case study was used to test the efficiency of the proposed DAG-BRB. The results showed that compared with other detection models, the DAG-BRB model has a higher detection rate and can be used in real networks.

• Journal of Pharmacopuncture
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• v.20 no.2
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• pp.119-126
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• 2017

Objectives: Semecarpus anacardium Linn. is a plant well-known for its antimicrobial, antidiabetic and anti-arthritic properties in the Ayurvedic and Siddha system of medicine. This has prompted the screening of this plant for antibacterial activity. The main aims of this study were to isolate compounds from the plant's seeds and to evaluate their antibacterial effects on clinical bacterial test strains. Methods: The n-butanolic concentrate of the seed extract was subjected to thin layer chromatography (TLC) and repeated silica gel column chromatography followed by elution with various solvents. The compound was identified based on observed spectral (IR, $^1H$ NMR, $^{13}C$ NMR and high-resolution mass spectrometry) data. The well diffusion method was employed to evaluate the antibacterial activities of the isolated acyclic isoprenoid compound (final concentration: $5-15{\mu}g/mL$) on four test bacterial strains, namely, Staphylococcus aureus (MTCC 96), Bacillus cereus (MTCC 430), Escherichia coli (MTCC 1689) and Acinetobacter baumannii (MTCC 9829). Results: Extensive spectroscopic studies showed the structure of the isolated compound to be an acyclic isoprenoid ($C_{21}H_{32}O$). Moreover, the isoprenoid showed a remarkable inhibition of bacterial growth at a concentration of $15{\mu}g/mL$ compared to the two other doses tested (5 and $10{\mu}g/mL$) and to tetracycline, a commercially available antibiotic that was used as a reference drug. Conclusion: The isolation of an antimicrobial compound from Semecarpus anacardium seeds validates the use of this plant in the treatment of infections. The isolated compound found to be active in this study could be useful for the development of new antimicrobial drugs.

• Journal of the Korean Chemical Society
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• v.39 no.1
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• pp.66-70
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• 1995

The soil humic acid was subdivided into four subfractions by molecular weight (F1: >100.000 dalton; F2: >100.000 dalton; F3: >10.000 dalton; F4: >2.000 dalton) using MP-dual hollow fiber ultrafiltration system. The characterization using IR, 1H and 13C NMR spectroscopy, showed similar spectroscopic features of HA, demonstrating that the bulk properties of HA subfractions are very similar to one another. IR spectral data showed a decrease in polysaccharide contents and increase in carboxylate functionality as molecular weight become smaller.functions. The structure of (NO) can be described by two interactions (N${\cdot}{\cdot}{\cdot}$N, N${\cdot}{\cdot}{\cdot}$O). One is the ONNO structure with an (N${\cdot}{\cdot}{\cdot}$N) interaction. In this structure, acyclic cis-ONNO with $C_{2v}$-symmetry, acyclic trans-ONNO with $C_{2h}$, and cyclic ONNO with trapezoidal structure ($C_{2v}$) are optimized at the MP2 level. The other structure is the ONON structure with an (N${\cdot}{\cdot}{\cdot}$O) interaction. In the structure, acyclic cis-ONON with Cs$^{-symmetry}$ and cyclic ONON of the rectangular ($C_{2h}$), square $(D_{2h})$, rhombic $(D_{2h})$, and parallelogramic $(D_{2h})$ geometries are also optimized. It is found that acyclic cis-ONNO $(^1A_1$) is the most stable structure and cyclic ONNO ($^3A_1$) is the least stable. Acyclic trans-ONNO ($^3A_1$) with an (N${\cdot}{\cdot}{\cdot}$N) interaction, acyclic trans-ONON and bicyclic ONON $(C_{2v})$ with (N${\cdot}{\cdot}{\cdot}$O) interaction, and acyclic cis- and trans-NOON with an (O${\cdot}{\cdot}{\cdot}$O) interaction can not be optimized at the MP2 level. Particularly, acyclic trans-ONNO with $C_{2h}$-symmetry can not be optimized at the CCSD(T) level. Meanwhile, acyclic NNOO ($^1A_1$, $C_s)$ and trianglic NNOO ($^1A_1$,$C_{2v})$ formed by the (O${\cdot}{\cdot}{\cdot}$N) interaction between $O_2$and $N_2$are optimized at the MP2 level. The binding energies and the relative energy gaps among the isomers are found to be relatively small./sec. Spiral CT scans during the arterial phase were obtained 35 seconds after the injection of contrast medium. CT findings of 78 lesions less than 4cm in diameter were correlated with angiographic findings. Results : The attenuation of lesions was high(n = 69), iso(n = 5), and low(n = 4) compared with liver parenchyma during the arterial phase of spiral CT. In lesions with high-, iso-, and low-attenuation during the arterial phase of spiral CT, hypervascularity on angiograms was found in 63 of 69(91.3%), three of five(60%), and three of four lesions(75%), respectively. Six lesions with high-attenuation on the arterial phase of spiral CT were not seen on angiography. Two iso-attenuated and one low-attenuated lesion were hypovascular on angiograms. Conclusion : The results of this study suggest that with some exceptions there was good correlation between the arterial phase of spiral CT and angiography.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.8
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• pp.149-156
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• 2021

Gambling negatively affects the economy, and it brings unwanted financial, social, and health outcomes to gamblers. On the one hand, unemployment is argued to be a leading cause of gambling. On the other hand, gambling can cause unemployment in the second-order via gambling-induced poor health, falling productivity, and crime. In terms of significant effects, previous studies were able to establish an association, but not causality. The current study examines the time-sequence and contemporaneous causalities between lottery gambling and unemployment in Thailand. The Granger causality and directed acyclic graph (DAG) tests employ time-series data on gambling- and unemployment-related Google Trends indexes from January 2004 to April 2021 (208 monthly observations). These tests are based on the estimates from a vector autoregressive (VAR) model. Granger causality is a way to investigate causality between two variables in a time series. However, this approach cannot detect the contemporaneous causality among variables that occurred within the same period. The contemporaneous causal structure of gambling and unemployment was identified via the data-determined DAG approach. The use of time-series Google Trends indexes in gambling studies is new. Based on this data set, unemployment is found to contemporaneously cause gambling, whereas gambling Granger causes unemployment. The causalities are circular and last for four months.

• Journal of Korea Port Economic Association
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• v.30 no.2
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• pp.77-92
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• 2014

The focus of this study is to analyse dynamic relationship among BDI(Baltic Dry-bulk Index, hereafter BDI), forex market and industrial production using monthly data from 2003-2013. Specifically, we have focused on the investigations how monetary and real variable affect shipping industry during recession period. To compare performance between general VAR and Bayesian VAR we first examine DAG(Directed Acyclic Graph) to clarify causality among the variables and then employ MSFE(mean squared forecast error). The overall estimated results from impulse-response analysis imply that BDI has been strongly affected by other shock, such as forex market and industrial production in Bayesian VAR. In particular, Bayesian VAR show better performance than general VAR in forecasting.