• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.4
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• pp.1224-1248
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• 2022

In various sensor network applications, such as climate observation organizations, sensor nodes need to collect information from time to time and pass it on to the recipient of information through multiple bounces. According to field tests, this information corresponds to most of the energy use of the sensor hub. Decreasing the measurement of information transmission in sensor networks becomes an important issue.Compression sensing (CS) can reduce the amount of information delivered to the network and reduce traffic load. However, the total number of classification of information delivered using pure CS is still enormous. The hybrid technique for utilizing CS was proposed to diminish the quantity of transmissions in sensor networks.Further the energy productivity is a test task for the sensor nodes. However, in previous studies, a clustering approach using hybrid CS for a sensor network and an explanatory model was used to investigate the relationship between beam size and number of transmissions of hybrid CS technology. It uses efficient data integration techniques for large networks, but leads to clone attacks or attacks. Here, a new algorithm called SBEA (Snowball Endurance Algorithm) was proposed and tested with a bow. Thus, you can extend the battery life of your WSN by running effective copy detection. Often, multiple nodes, called observers, are selected to verify the reliability of the nodes within the network. Personal data from the source centre (e.g. personality and geographical data) is provided to the observer at the optional witness stage. The trust and reputation system is used to find the reliability of data aggregation across the cluster head and cluster nodes. It is also possible to obtain a mechanism to perform sleep and standby procedures to improve the life of the sensor node. The sniffers have been implemented to monitor the energy of the sensor nodes periodically in the sink. The proposed algorithm SBEA (Snowball Endurance Algorithm) is a combination of ERCD protocol and a combined mobility and routing algorithm that can identify the cluster head and adjacent cluster head nodes.This algorithm is used to yield the network life time and the performance of the sensor nodes can be increased.

• Journal of the Korean Society of Food Science and Nutrition
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• v.42 no.6
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• pp.837-843
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• 2013

Sasa borealis is a major source of bamboo leaves used for traditional medicine in Korea. Obesity is a serious health problem in industrialized countries that has been implicated in various diseases, including type 2 diabetes, hypertension, cancer, and coronary heart disease. Recent reports have proposed mechanisms to reduce obesity by decreasing preadipocyte differentiation, and proliferation in 3T3-L1 preadipocyte. The preadipocytes play a key role by differentiation into mature adipocytes and increasing fat mass. In this study, we investigated whether ethanol-soluble extracts and ethyl acetate-soluble fractions from Sasa borealis inhibits intracellular accumulation of lipid droplets in a dose-dependent manner in 3T3-L1 cells (an important model system for studying adipogenesis). The down-regulation of PPAR${\gamma}$ and C/EBP${\alpha}$ (key adipogenic transcription factors) were confirmed by the reverse transcription polymerase chain reaction (RT-PCR). Ethyl acetate-soluble fractions from Sasa borealis attenuated the expression of PPAR${\gamma}$ and C/EBP${\alpha}$. These results suggest that Sasa borealis inhibits adipogenic differentiation by regulating adipogenic transcription factors in 3T3-L1 cells. Therefore, Sasa borealis extracts may be a good candidate for the management of obesity.