• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.3
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• pp.439-444
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• 2017

Wireless sensor network technology is a rapidly growing technology of ubiquitous computing environment and application and research are being carried out in various fields. The sensor nodes constituting the wireless sensor network maintain the life cycle by using the battery in the distributed network environment, so energy efficiency is more important than QoS requirement. In MAC protocol of IEEE802.15.4, MAC protocol study adaptive to traffic and standardization work emphasizing reliability and efficiency in wireless sensor network environment are underway. but, Wireless sensor networks have the problem that the response speed of the sensor node drops as the energy efficiency decreases. In this paper, we designed the MAC protocol with improved energy efficiency of the whole network by analyzing the MAC protocol of the synchronous method and the hybrid method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.4
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• pp.1437-1459
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• 2020

Wireless Sensor Networks (WSN) is a distributed Sensor network whose terminals are sensors that can sense and check the environment. Sensors are typically battery-powered and deployed in where the batteries are difficult to replace. Therefore, maximize the consumption of node energy and extend the network's life cycle are the problems that must to face. Low-energy adaptive clustering hierarchy (LEACH) protocol is an adaptive clustering topology algorithm, which can make the nodes in the network consume energy in a relatively balanced way and prolong the network lifetime. In this paper, the novel multi-objective LEACH protocol is proposed, in order to solve the proposed protocol, we design a multi-objective coupling algorithm based on bat algorithm (BA), glowworm swarm optimization algorithm (GSO) and bacterial foraging optimization algorithm (BFO). The advantages of BA, GSO and BFO are inherited in the multi-objective coupling algorithm (MBGF), which is tested on ZDT and SCH benchmarks, the results are shown the MBGF is superior. Then the multi-objective coupling algorithm is applied in the multi-objective LEACH protocol, experimental results show that the multi-objective LEACH protocol can greatly reduce the energy consumption of the node and prolong the network life cycle.

• Computers and Concrete
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• v.10 no.6
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• pp.587-607
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• 2012

The purpose of this research is to propose a design technique of concrete mix proportions satisfying service life through genetic algorithm (GA) and neural network (NN). For this, thirty mix proportions and the related diffusion coefficients in high performance concrete are analyzed and fitness function for diffusion coefficient is obtained considering mix components like w/b (water to binder ratio), cement content, mineral admixture (slag, flay ash and silica fume) content, sand and coarse aggregate content. Through averaging the results of 10 times GA simulations, relative errors to the previous data decrease lower than 5.0% and the simulated mix proportions are verified with the experimental results. Assuming the durability design parameters, intended diffusion coefficient for intended service life is derived and mix proportions satisfying the service life are obtained. Among the mix proportions, the most optimized case which satisfies required concrete strength and the lowest cost is selected through GA algorithm. The proposed technique would be improved with the enhancement of comprehensive data set including wider the range of diffusion coefficients.

• Proceedings of the Korea Society for Simulation Conference
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• 2005.11a
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• pp.171-179
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• 2005

Computer virus modeling and simulation research has been conducted with focus on the network vulnerability analysis. However, computer virus generally shows the biological virus characters such as proliferation, reproduction and evolution. Therefore it is necessary to research the computer virus modeling and simulation using Artificial Life. The approach of computer modeling and simulation using the Artificial Life technology Provides the efficient analysis method for the effects on the network by computer virus and the behavioral mechanism of the computer virus. Hence this paper proposes the methodology of computer virus modeling and simulation using Artificial Life, which may be contribute the research on the computer virus vaccine.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.3
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• pp.774-780
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• 2010

USN(Ubiquitous Sensor Network) is a core infrastructure that u-life use to enable the realization in the ubiquitous society through various services of area such as u-city, u-Health. Therefore, we need a research for domestic standards to establish USN technique. Currently, status of USN standards is most standard and research that it is a technology for sensor node implementation and a protocol for energy-efficient communication and interlock with existing network. But, Standard and research for sensor network and integration management of heterogeneous sensor networks for USN application and sensing data management and USN database structure definition such as application and middleware is weak level. In this paper, we researched for standard development of domestic a sensor network and the relevant standard analysis to configure SWE(Sensor Web Enablement) of OGC(Open Geospatial Consortium) for standarded plattform technology. Also we researched that it's a connection between domestic ITA(Telecommunications Technology Association) standards and SWE Standard.

• Research in Community and Public Health Nursing
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• v.24 no.4
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• pp.438-450
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• 2013

Purpose: The purpose of this study is to identify relationships between acculturation, social network, and health-related quality of life (HRQOL) among Korean-Chinese immigrants. Methods: A cross-sectional descriptive study was conducted with 147 Korean-Chinese immigrants who were residing more than 1 year in Korea. Physical and mental dimensions of HRQOL were assessed by Short Form-12 Health Survey that consisted of a physical component summary (PCS) and a mental component summary (MCS). Data were analyzed with Pearson's correlation and multiple regression. Results: The mean PCS score was $41.14{\pm}10.72$ and the mean MCS score was $49.09{\pm}11.31$ (possible range 10-70). Depression (${\beta}$=-6.43) and Social network frequency (${\beta}$=2.44) explained 28.4% of the variance in PCS while depression (${\beta}$=-11.54) and visiting clinic/hospital (${\beta}$=-4.00) explained 34.3% of the variance in MCS. Acculturation was not significantly associated with HRQOL. Conclusion: This study confirmed that the social network frequency influences HRQOL among Korean-Chinese Immigrants. The findings suggest that social network analysis should be considered in the process of developing health intervention strategies for Korean-Chinese immigrants.

• Journal of Ecology and Environment
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• v.47 no.4
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• pp.219-227
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• 2023

The US National Science Foundation's National Ecological Observatory Network (NEON) is a continental-scale program intended to provide open data, samples, and infrastructure to understand changing ecosystems for a period of 30 years. NEON collects co-located measurements of drivers of environmental change and biological responses, using standardized methods at 81 field sites to systematically sample variability and trends to enable inferences at regional to continental scales. Alongside key atmospheric and environmental variables, NEON measures the biodiversity of many taxa, including microbes, plants, and animals, and collects samples from these organisms for long-term archiving and research use. Here we review the composition and use of NEON resources to date as a whole and specific to biodiversity as an exemplar of the potential of national research infrastructure to contribute to globally relevant outcomes. Since NEON initiated full operations in 2019, NEON has produced, on average, 1.4 M records and over 32 TB of data per year across more than 180 data products, with 85 products that include taxonomic or other organismal information relevant to biodiversity science. NEON has also collected and curated more than 503,000 samples and specimens spanning all taxonomic domains of life, with up to 100,000 more to be added annually. Various metrics of use, including web portal visitation, data download and sample use requests, and scientific publications, reveal substantial interest from the global community in NEON. More than 47,000 unique IP addresses from around the world visit NEON's web portals each month, requesting on average 1.8 TB of data, and over 200 researchers have engaged in sample use requests from the NEON Biorepository. Through its many global partnerships, particularly with the Global Biodiversity Information Facility, NEON resources have been used in more than 900 scientific publications to date, with many using biodiversity data and samples. These outcomes demonstrate that the data and samples provided by NEON, situated in a broader network of national research infrastructures, are critical to scientists, conservation practitioners, and policy makers. They enable effective approaches to meeting global targets, such as those captured in the Kunming-Montreal Global Biodiversity Framework.

• Proceedings of the Korean Society for Applied Microbiology Conference
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• 2002.10a
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• pp.32-32
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• 2002

• IMMUNE NETWORK
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• v.9 no.1
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• pp.1-3
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• 2009

• Proceedings of the Korean Society of Life Science Conference
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• 2006.09a
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• pp.78.1-78.1
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• 2006