• Journal of Communications and Networks
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• v.12 no.1
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• pp.11-18
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• 2010

Diversity-multiplexing tradeoff (DMT) is an efficient tool to measure the performance of multiple-input and multiple-output (MIMO) systems and cooperative systems. Recently, cooperative multicast system with wireless network coding stretched tremendous interesting due to that it can drastically enhance the throughput of the wireless networks. It is desirable to apply DMT to the performance analysis on the multicast system with wireless network coding. In this paper, DMT is performed at the three proposed wireless network coding protocols, i.e., non-regenerative network coding (NRNC), regenerative complex field network coding (RCNC) and regenerative Galois field network coding (RGNC). The DMT analysis shows that under the same system performance, i.e., the same diversity gain, all the three network coding protocols outperform the traditional transmission scheme without network coding in terms of multiplexing gain. Our DMT analysis also exhibits the trends of the three network coding protocols' performance when multiplexing gain is changing from the lower region to the higher region. Monte-Carlo simulations verify the prediction of DMT.

• Genomics & Informatics
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• v.5 no.3
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• pp.133-136
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• 2007

The Gene Set network viewer (GSnet) visualizes the functional enrichment of a given gene set with a protein interaction network and is implemented as a plug-in for the Cytoscape platform. The functional enrichment of a given gene set is calculated using a hypergeometric test based on the Gene Ontology annotation. The protein interaction network is estimated using public data. Set operations allow a complex protein interaction network to be decomposed into a functionally-enriched module of interest. GSnet provides a new framework for gene set analysis by integrating a priori knowledge of a biological network with functional enrichment analysis.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.191-197
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• 2021

Ensuring the economic security of agro-industrial complexes of Ukrainian regions has become a top-priority task of state regional policy, as their stable functioning is an essential element of economic security of the whole country. It is overcoming threats to the development of the agro-industrial complex that ensures its further effective functioning and has a significant impact on the economic security of our state. Methods: logical method; methods of system analysis; synthesis; economic and statistical method; method of expert assessment; SWOT analysis; economic and mathematical modelling and planning. Results. Characteristic features of economic security have been given. The essence and significance of the agro-industrial complex in improving the economic security of the state have been determined. It has been noted that in recent years, the agro-industrial complex, which acts as a driver of the domestic economy and has a direct impact on the development of the country, has been growing (in 2019 the cereal and legume harvest exceeded 75 million tons, 20,269 thousand tons of potatoes were dug, more than 15 million tons of sunflower, 9,688 thousand tons of vegetables and 2,119 thousand tons of fruits and berries were harvested, meat and egg production increased by 137.5 thousand tons (or 5.8%) and 545.5 million pieces (or 3.4%), respectively, the number of employed population in agriculture increased by 139.8 thousand people (or 4.9%), the labour productivity in crop production increased by UAH 294.4 thousand (or 44.6%), in livestock production - by UAH 311.3 thousand (or 61.8%)). Based on the system of production and economic indicators, the analysis of the state of the agro-industrial complex has been carried out. Taking into account the results of the obtained data and using SWOT-analysis, the major threats to the development of the agro-industrial complex have been identified. Ways of overcoming threats enhancing the economic security of Ukraine have been proposed.

• Journal of Korean Tunnelling and Underground Space Association
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• v.19 no.2
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• pp.213-229
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• 2017

Recently, in urban areas there is a tendency to construct more complex network-type tunnels including entrance and exit ramps. At the same time, various one-dimensional programs based on the network theory have been proposed for tunnel ventilation analysis. This paper aims at developing a program that can analyze the ventilation flow rate and pollutants concentration in complex network-type tunnels based on the none hardy-cross method. The flow analysis in the branch was carried out on the basis of the Gradient method, while for the concentration analysis a new logic has been developed to calculate the inflow and outflow concentration automatically in a complex network-type structure. Additionally, in the tunnel segments showing low flow rate, proper grid interval sizes were proposed to reduce numerical error. To verify the applicability of the program, flow rates predicted in the straight tunnels were compared with the classical velocity-diagram method by Stokic and the TVSDM program. The results showed that the errors were within 1%. In addition, the program was applied to the recent ventilation system adopted in the complex network-type urban tunnels.

• Journal of the Korean Society for Precision Engineering
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• v.27 no.9
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• pp.103-110
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• 2010

This paper presents the optimized approximation of finite element modeling for a complex tool holder spindle using both DOE (Design of Experiment) with Optimal Latin Hypercube (OLH) method and approximation modeling method with Radial Basis Function (RBF) neural network structure. The complex tool holder is used for holding a (milling/drilling) tool of a machine tool. The engineering problem of complex tool holder results from the twisting of spindle of tool holder. For this purpose, we present the optimized approximation of finite element modeling for a complex tool holder spindle using both DOE (Design of Experiment) with Optimal Latin Hypercube (OLH) method (specifically a module of $iSight^{(R)}$ FD-3.1) and approximation modeling method with Radial Basis Function (RBF) (another module of $iSight^{(R)}$ FD-3.1) neural network structure

• Korean Journal of Construction Engineering and Management
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• v.20 no.1
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• pp.105-113
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• 2019

A construction project is a complex process consisting of interdependent tasks. If one task has variation, other tasks will be affected additionally and it is difficult to reach consensus on task variation due to the characteristics of the construction site that is going on quickly and complicatedly. Therefore, this study identified the root cause of task variation in construction process. Adjacent matrix was created with the tasks corresponding to major causes of variation, and the network analysis was performed. The results of social network analysis in the construction process can stabilize the work flow in the complex process and improve the reliability of the process plan and the project performance.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.05a
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• pp.191-194
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• 2001

The ozone forecasting systems have many problems because the mechanism of the ozone concentration is highly complex, nonlinear, and nonstationary. Also, the results of prediction are not a good performance so far, especially in the high-level ozone concentration. This paper describes the modeling method of the ozone prediction system using neuro-fuzzy approaches and fuzzy clustering. The dynamic polynomial neural network (DPNN) based upon a typical algorithm of GMDH (group method of data handling) is a useful method for data analysis, identification of nonlinear complex system, and prediction of a dynamical system.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.07a
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• pp.699-700
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• 2021

This study investigated patterns of co-occuring chronic diseases and disorders in old ages. For this purpose, we utilized data from the Korean National Health and Nutrition Examination Survey for 3,734 old adults aged over 65. Data on 18 conditions were obtained, and analyzed using network analysis, associated rule mining, cluster analysis. The majority of participants has multimorbidity. Association rules analysis reveals unexpected comorbidities with high lift and confidence. Also, some morbidity clusters were present. Diabetes and emotional disorder had the greatest comorbidity and represent complex comorbid conditions. Old age is characterized by a complex pattern of multimorbidity and comorbidity. In conclusion, particular combinations of morbidities were very prevalent and will be needed to policy of health care interventions for old ages.

• The Journal of the Korea Contents Association
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• v.3 no.2
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• pp.19-23
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• 2003

Neurons in the mammalian visual cortex can be dassified into the two main categories of simple cells and complex cells based on their response properties. Here, we find the complex features corresponding to the response of complex cells by applying the unsupervised independent component analysis network to input images. This result will be helpful to elucidate the information processing mechanism of neurons in primary visual cortex.

• The Journal of the Korea Contents Association
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• v.10 no.7
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• pp.420-428
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• 2010

The advancement of the Science for complex systems enables the analysis of many social networks. We constructed and analyzed a Korean movie star network as one of social networks, based on the 100 Korean movie selection for a main data source. Until now, the research trend has been the structural analysis of network, focused on link numbers, such as degree, betweenness and clustering coefficient. But it is time that the research is not limited by the structural analysis of networks only. Rather, the research goal should be aimed to an information analysis, performed by identifying and analyzing central modules that are regarded as the core of complex networks, using k-core analysis method. In this research, we constructed a network of movie stars who have appeared in 100 Korean movie selection, provided by Korean movie database, also we analyzed its core modules with and without weights, and the trend of seasonal expansion of the network. We expect our findings can be used as the basic data applicable to a model for understanding of the expansion and evolution of networks.