• Korean Journal of Exercise Nutrition
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• v.25 no.3
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• pp.28-35
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• 2021

[Purpose] As Panax ginseng C. A. Meyer (ginseng) exhibits various physiological activities and is associated with exercise, we investigated the potential active components of ginseng and related target genes through network pharmacological analysis. Additionally, we analyzed the association between ginseng-related genes, such as the G-protein-coupled receptors (GPCRs), and improved exercise capacity. [Methods] Active compounds in ginseng and the related target genes were searched in the Traditional Chinese Medicine Database and Analysis Platform (TCMSP). Gene ontology functional analysis was performed to identify biological processes related to the collected genes, and a compound-target network was visualized using Cytoscape 3.7.2. [Results] A total of 21 ginseng active compounds were detected, and 110 targets regulated by 17 active substances were identified. We found that the active compound protein was involved in the biological process of adrenergic receptor activity in 80%, G-protein-coupled neurotransmitter in 10%, and leucocyte adhesion to arteries in 10%. Additionally, the biological response centered on adrenergic receptor activity showed a close relationship with G protein through the beta-1 adrenergic receptor gene reactivity. [Conclusion] According to bioavailability analysis, ginseng comprises 21 active compounds. Furthermore, we investigated the ginseng-stimulated gene activation using ontology analysis. GPCR, a gene upregulated by ginseng, is positively correlated to exercise. Therefore, if a study on this factor is conducted, it will provide useful basic data for improving exercise performance and health.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.2D
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• pp.147-154
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• 2008

A variety of activity happens around the sidewalk in the city. Particularly, a large variety of activity happens in shopping area, but it causes an obstruction of economical revitalization since the pedestrians require time and cost to find what they want. So, this study will develop the path searching method to minimize the economical loss of shoppers by providing the significant path and supporting the walking movement. Firstly, consider existing network expression techniques and approach three points which are physical and environmental factor, the recognition of the pedestrians' space when changing the direction, and the recognition of restriction of vision and accessibility. Try to design the network DB and simulate the algorithm. As a result, it is now possible to do the path searching that considers variety of recognition factors and show the method how to make the path-searching algorithm for pedestrian.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.10
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• pp.89-100
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• 2007

Consumer Portal is defined as "a combination of hardware and software that enables two-way communication between energy service provider(ESP, like KEPCO) and equipment within the consumer's premises". The portal provides both a physical link(between wires, radio waves, and other media) and a logical link(translating among language-like codes and etiquette-like protocols) between in-building and wide-area access networks. Thus, the consumer portal is an important, open public shared infrastructure in the future vision of energy services. In this paper, we describe a new methodology for local communication and computer network capacity design of consumer portal, and also presents capacity calculation method using a network system limitation factors. By the approach, we can check into the limitations of existing methods, and propose an improved data processing algorithm that can expand the maximum number of the networked end-use devices up to $30{\sim}40$ times. For validation, we applies the proposed methode to our real system design. Our contribution will help electrical power information network design.

• The Journal of Engineering Geology
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• v.15 no.1
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• pp.67-76
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• 2005

This paper presents the application of a neural network for prediction of the unconfined compressive strength from physical properties and schmidt hardness number on rock samples. To investigate the suitability of this approach, the results of analysis using a neural network are compared to predictions obtained by statistical relations. The data sets containing 55 rock sample records which are composed of sandstone and shale were assembled in Daegu area. They were used to learn the neural network model with the back-propagation teaming algorithm. The rock characteristics as the teaming input of the neural network are: schmidt hardness number, specific gravity, absorption, porosity, p-wave velocity and S-wave velocity, while the corresponding unconfined compressive strength value functions as the teaming output of the neural network. A data set containing 45 test results was used to train the networks with the back-propagation teaming algorithm. Another data set of 10 test results was used to validate the generalization and prediction capabilities of the neural network.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.4
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• pp.284-288
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• 2009

With explosively growing PPI databases, the computational approach for a prediction and configuration of PPI network has been a big stream in the bioinformatics area. Recent researches gradually consider physicochemical properties of proteins and support high resolution results with integration of experimental results. With regard to current research trend, it is very close future to complete a PPI network configuration of each organism. However, direct applying the PPI network to real field is complicated problem because PPI network is only a set of co-expressive proteins or gene products, and its network link means simple physical binding rather than in-depth knowledge of biological process. In this paper, we suggest a protein functional flow model which is a directed network based on a protein functions' relation of signaling transduction pathway. The vertex of the suggested model is a molecular function annotated by gene ontology, and the relations among the vertex are considered as edges. Thus, it is easy to trace a specific function's transition, and it can be a constraint to extract a meaningful sub-path from whole PPI network. To evaluate the model, 11 functional flow models of Homo sapiens were built from KEGG, and Cronbach's alpha values were measured (alpha=0.67). Among 1023 functional flows, 765 functional flows showed 0.6 or higher alpha values.

• Journal of Satellite, Information and Communications
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• v.9 no.1
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• pp.51-56
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• 2014

High-availability seamless redundancy (HSR) is a protocol for fault-tolerant Ethernet (FTE) networks. It provides two frame copies and each copy is forwarded on a separate physical path, which provides zero fail-over time. Therefore, the HSR is becoming a potential candidate for various real-time FTE applications. However, the generation and circulation of unnecessary frames due to the duplication of every sending frame is inherent drawback of HSR. Such drawback degrades the performance of the network and may deplete its resources. In this paper, we present a new algorithm called port locking (PL) based on the media access control (MAC) address to solve the abovementioned problem in popular connected-rings network. Our approach makes the network gradually learn the locations of the source and the destination nodes without relying on network control frames. It then prunes all the rings that do not contain the destination node by locking corresponding rings' entrance ports. With the PL algorithm, the traffic can be significantly reduced and therefore the network performance will be greatly enhanced specially in a large scale connected-rings network. Analytical results are provided to validate the PL algorithm.

• Journal of the Korean Institute of Educational Facilities
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• v.19 no.2
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• pp.59-66
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• 2012

Community design education has covered the worldview dimension of the collaborative courses for sustainability draws on the architectural expertise developed in a network of community projects and therefore case studies of design education by the collaborative project-based learning in terms of participants, students, teachers and architects, such as 'Learning By Design' for the K-12 comprehensive program in Massachusetts addresses how a local society can make its community sustainable by both design and education. To understand that community design and education can provide professional development in all levels of skills and knowledge across disciplines and opportunities for collaborative learning and problem-solving, this research consists of case studies of the community design education including social systems that assist in organizing the local educational program as well as promoting the programs with public awareness of the community. It covers the UNESCO-UIA agenda of the community design and education that is to enhance the physical environment relating to human interaction by developing innovative alternatives of existing community and contributing voluntarily to neighborhoods through design. As the community design collaborative of design professionals and users is a structural approach to assess design quality, the cases address how to set up the architectural program in order to share pro bono design service and provide high-quality design resources available for sustainable environment.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.4
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• pp.389-394
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• 2006

Inaccurate localization exposes a robot to many dangerous conditions. It could make a robot be moved to wrong direction or damaged by collision with surrounding obstacles. There are numerous approaches to self-localization, and there are different modalities as well (vision, laser range finders, ultrasonic sonars). Since sensor information is generally uncertain and contains noise, there are many researches to reduce the noise. But, the correctness is limited because most researches are based on statistical approach. The goal of our research is to measure more exact robot location by matching between built VRML 3D model and real vision image. To determine the position of mobile robot, landmark-localization technique has been applied. Landmarks are any detectable structure in the physical environment. Some use vertical lines, others use specially designed markers, In this paper, specially designed markers are used as landmarks. Given known focal length and a single image of three landmarks it is possible to compute the angular separation between the lines of sight of the landmarks. The image-processing and neural network pattern matching techniques are employed to recognize landmarks placed in a robot working environment. After self-localization, the 2D scene of the vision is overlaid with the VRML scene.

• Journal of Electrical Engineering and Technology
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• v.9 no.6
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• pp.2142-2153
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• 2014

Linearization of transducer characteristic plays a vital role in electronic instrumentation because all transducers have outputs nonlinearly related to the physical variables they sense. If the transducer output is nonlinear, it will produce a whole assortment of problems. Transducers rarely possess a perfectly linear transfer characteristic, but always have some degree of non-linearity over their range of operation. Attempts have been made by many researchers to increase the range of linearity of transducers. This paper presents a method to compensate nonlinearity of Linear Variable Displacement Transducer (LVDT) based on Extreme Learning Machine (ELM) method, Differential Evolution (DE) algorithm and Artificial Neural Network (ANN) trained by Genetic Algorithm (GA). Because of the mechanism structure, LVDT often exhibit inherent nonlinear input-output characteristics. The best approximation capability of optimized ANN technique is beneficial to this. The use of this proposed method is demonstrated through computer simulation with the experimental data of two different LVDTs. The results reveal that the proposed method compensated the presence of nonlinearity in the displacement transducer with very low training time, lowest Mean Square Error (MSE) value and better linearity. This research work involves less computational complexity and it behaves a good performance for nonlinearity compensation for LVDT and has good application prospect.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.4
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• pp.1282-1301
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• 2015

Traditional infrastructure has been superseded by cloud computing, due to its cost-effective and ubiquitous computing model. Cloud computing not only brings multitude of opportunities, but it also bears some challenges. One of the key challenges it faces is recovery of computing nodes, when an Information Technology (IT) failure occurs. Since cloud computing mainly depends upon its nodes, physical servers, that makes it very crucial to recover a failed node in time and seamlessly, so that the customer gets an expected level of service. Work has already been done in this regard, but it has still proved to be trivial. In this study, we present a Cost-Time aware Genetic scheduling algorithm, referred to as CTaG, not only to globally optimize the performance of the cloud system, but also perform recovery of failed nodes efficiently. While modeling our work, we have particularly taken into account the factors of network bandwidth and customer's monetary cost. We have implemented our algorithm and justify it through extensive simulations and comparison with similar existing studies. The results show performance gain of our work over the others, in some particular scenarios.