• Journal of Broadcast Engineering
• /
• v.24 no.2
• /
• pp.251-263
• /
• 2019

Recently the huge demand for Internet media streaming has dramatically increased the cost of the CDN (Content Delivery Network) and the need for a means to reduce it is increasing day by day. In this situation, a P2P-assisted DASH technology has recently emerged, which uses P2P (Peer-to-Peer) communications based on WebRTC (Web Real-Time Communication) standards to reduce the CDN cost. This paper proposes an algorithm that can significantly improve CDN cost savings in this technology by selecting peers based on the transport history. Also we implemented this algorithm in an experimental system and, after setting experimental conditions that emulate the actual mobile network environment, we measured the performance of the experimental system. As a result, we demonstrated that the proposed algorithm can achieve higher CDN cost savings compared to the conventional algorithm where peers are selected at random.

• Journal of Animal Science and Technology
• /
• v.63 no.6
• /
• pp.1411-1422
• /
• 2021

Lactobacillus acidophilus is a gram-positive, microaerophilic, and acidophilic bacterial species. L. acidophilus strains in the gastrointestinal tracts of humans and other animals have been profiled, but strains found in the canine gut have not been studied yet. Our study helps in understanding the genetic features of the L. acidophilus C5 strain found in the canine gut, determining its adaptive features evolved to survive in the canine gut environment, and in elucidating its probiotic functions. To examine the canine L. acidophilus C5 genome, we isolated the C5 strain from a Korean dog and sequenced it using PacBio SMRT sequencing technology. A comparative genomic approach was used to assess genetic relationships between C5 and six other strains and study the distinguishing features related to different hosts. We found that most genes in the C5 strain were related to carbohydrate transport and metabolism. The pan-genome of seven L. acidophilus strains contained 2,254 gene families, and the core genome contained 1,726 gene families. The phylogenetic tree of the core genes in the canine L. acidophilus C5 strain was very close to that of two strains (DSM20079 and NCFM) from humans. We identified 30 evolutionarily accelerated genes in the L. acidophilus C5 strain in the ratio of non-synonymous to synonymous substitutions (dN/dS) analysis. Five of these thirty genes were associated with carbohydrate transport and metabolism. This study provides insights into genetic features and adaptations of the L. acidophilus C5 strain to survive the canine intestinal environment. It also suggests that the evolution of the L. acidophilus genome is closely related to the host's evolutionary adaptation process.

• Journal of the Korean Society of Groundwater Environment
• /
• v.6 no.1
• /
• pp.23-32
• /
• 1999

A new numerical method using solution-adaptive grids (SAG) is developed to solve the Richards' equation (RE) for unsaturated flow in porous media. Using a grid generation technique, the SAG method automatically redistributes a fixed number of grid points during the flow process, so that more grid points are clustered in regions of large solution gradients. The method uses the coordinate transformation technique to employ a new transformed RE, which is solved with the standard finite difference method. The movement of grid points is incorporated into the transformed RE, and therefore all computation is performed on fixed grid points of the transformed domain without using any interpolation techniques. Thus, numerical difficulties arising from the movement of the wetting front during the infiltration process have been substantially overcome by the new method. Numerical experiments for an one-dimensional infiltration problem are presented to compare the SAG method to the modified Picard method using a fixed grid. Results show that accuracy of a SAG solution using 41 nodes is comparable with the solution of the fixed grid method using 201 nodes, while it requires only 50% of the CPU time. The global mass balance and the convergence of SAG solutions are strongly affected by the time step size (Δt) and the weighting parameter (${\gamma}$) used for generating solution-adaptive grids. Thus, the method requires automated readjustment of Δt and ${\gamma}$ to yield mass-conservative and convergent solutions, although it may increase computational costs. The method can be effective especially for simulating unsaturated flow and other transport problems involving the propagation of a sharp-front.

• Nuclear Engineering and Technology
• /
• v.52 no.11
• /
• pp.2452-2459
• /
• 2020

Neutron spectrum is essential to the safe operation of reactors. Traditional online neutron spectrum measurement methods still have room to improve accuracy for the application cases of wide energy range. From the application of artificial neural network (ANN) algorithm in spectrum unfolding, its accuracy is difficult to be improved for lacking of enough effective training data. In this paper, an adaptive deviation-resistant neutron spectrum unfolding method based on transfer learning was developed. The model of ANN was trained with thousands of neutron spectra generated with Monte Carlo transport calculation to construct a coarse-grained unfolded spectrum. In order to improve the accuracy of the unfolded spectrum, results of the previous ANN model combined with some specific eigenvalues of the current system were put into the dataset for training the deeper ANN model, and fine-grained unfolded spectrum could be achieved through the deeper ANN model. The method could realize accurate spectrum unfolding while maintaining universality, combined with detectors covering wide energy range, it could improve the accuracy of spectrum measurement methods for wide energy range. This method was verified with a fast neutron reactor BN-600. The mean square error (MSE), average relative deviation (ARD) and spectrum quality (Qs) were selected to evaluate the final results and they all demonstrated that the developed method was much more precise than traditional spectrum unfolding methods.

• Journal of Korea Water Resources Association
• /
• v.52 no.10
• /
• pp.681-695
• /
• 2019

A Transient Storage Model (TSM) is one of the most widely used model accounting for complex solute transport in natural river to understanding natural river properties with four TSM key parameters. The TSM parameters are estimated via inverse modeling. Parameter estimation of the TSM is carried out by solving optimization problem about finding best fitted simulation curve with measured curve obtained from tracer test. Several studies have reported uncertainty in parameter estimation from non-convexity of the problem. In this study, we assessed best combination of optimization method and objective function for TSM parameter estimation using Cheong-mi Creek tracer test data. In order to find best optimization setting guaranteeing convergence and speed, Evolutionary Algorithm (EA) based global optimization methods, such as CCE of SCE-UA and MCCE of SP-UCI, and error based objective functions were compared, using Shuffled Complex-Self Adaptive Hybrid EvoLution (SC-SAHEL). Overall results showed that multi-EA SC-SAHEL with Percent Mean Squared Error (PMSE) objective function is the best optimization setting which is fastest and stable method in convergence.

• World Technopolis Review
• /
• v.5 no.1
• /
• pp.47-60
• /
• 2016

In today's digital non-linear global business environment, innovation initiatives are influenced by inter-organizational, political, economic, environmental, technological systems, as well as by decisions made individually by key actors in these systems. Network-based structures emerge from social linkages and collaborations among various actors, creating innovation ecosystems, complex adaptive systems in which entities co-create value. A shared vision of value co-creation allows people operating individually to arrive together at the same future. Yet, relationships are difficult to see, continually changing and challenging to manage. The Innovation Ecosystem Transformation Framework construct includes three core components to make innovation relationships visible and articulate networks of relational capital for the wellbeing, sustainability and business success of innovation ecosystems: data-driven visualizations, storytelling and shared vision. Access to data facilitates building evidence-based visualizations using relational data. This has dramatically altered the way leaders can use data-driven analysis to develop insights and provide ongoing feedback needed to orchestrate relational capital and build shared vision for high quality decisions about innovation. Enabled by a shared vision, relational capital can guide decisions that catalyze, support and sustain an ecosystemic milieu conducive to innovation for business growth.

• BMB Reports
• /
• v.48 no.3
• /
• pp.139-146
• /
• 2015

Adaptive brain function and synaptic plasticity rely on dynamic regulation of local proteome. One way for the neuron to introduce new proteins to the axon terminal is to transport those from the cell body, which had long been thought as the only source of axonal proteins. Another way, which is the topic of this review, is synthesizing proteins on site by local mRNA translation. Recent evidence indicates that the axon stores a reservoir of translationally silent mRNAs and regulates their expression solely by translational control. Different stimuli to axons, such as guidance cues, growth factors, and nerve injury, promote translation of selective mRNAs, a process required for the axon's ability to respond to these cues. One of the critical questions in the field of axonal protein synthesis is how mRNA-specific local translation is regulated by extracellular cues. Here, we review current experimental techniques that can be used to answer this question. Furthermore, we discuss how new technologies can help us understand what biological processes are regulated by axonal protein synthesis in vivo.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2016.06a
• /
• pp.46-47
• /
• 2016

본 논문은 북미의 차세대 지상파 방송 표준인 ATSC 3.0에서 고려하고 있는 ROUTE(Real-time Object Delivery over Unidirectional Transport) 및 MPEG-DASH(Dynamic Adaptive Streaming over HTTP)를 기반으로 자유시점 방송 서비스를 송 수신하기 위한 SLS(Service Layer Signaling)을 제안한다. 특별히 ATSC 3.0과의 역호완성을 위하여 기존의 ROUTE/DASH의 SLS는 그대로 유지한 채 자유시점 방송을 위한 정보만 추가하여 기존의 SLS와 상호동작이 되도록 설계하였다. 따라서 본 논문에서 제안하는 내용은 향후 ATSC 3.0와 같이 IP(Internet Protocol)을 기반으로 SLS을 수행하는 표준규격과 역호환성을 유지한 채 자유시점 방송서비스를 할 수 있을 것으로 기대된다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.7
• /
• pp.2354-2370
• /
• 2015

The advantages of employing SCTP-based Concurrent Multipath Transfer (CMT) have been demonstrated to be very useful for data delivery over multi-homed wireless networks. However, there is still significant ongoing work addressing some remaining limitations and challenges. The most important concern when applying CMT to data delivery is related to handling packet reordering and buffer blocking. Another concern on this topic is that current sender-based CMT solutions seldom consider balancing the overhead and sharing the load between the sender and receiver. This paper proposes a novel Receiver-driven Cooperation-based Concurrent Multipath Transfer solution (CMT-Rev) with the following aims: (i) to balance overhead and share load between the sender and receiver, by moving some functions including congestion and flow control from the sender onto receiver; (ii) to mitigate the data reordering and buffer blocking problems, by using an adaptive receiver-cooperative path aggregation model, (iii) to adaptively transmit packets over multiple paths according to their receiver-inspired sending rate values, by employing a new receiver-aware data distribution scheduler. Simulation results show that CMT-Rev outperforms the existing CMT solutions in terms of data delivery performance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2000.05a
• /
• pp.470-473
• /
• 2000

The metal-oxide-semiconductor field-effect transistor(MOSFET) has undergone many changes in the last decade in response to the constant demand for increased speed, decreased power, and increased patting density. The devices are scaled down day by day. Therefore, This paper investigates how MOSFET structures influence on transport properties in according to change of channel length and bias and, observes impact ionization between the drain and the gate. This paper proposes three models, i.e., conventional MOSFET, LDD MOSFET and EPI MOSFET. The gate lengths are 0.3$\mu\textrm{m}$ 0.15$\mu\textrm{m}$, 0.075$\mu\textrm{m}$ and scaling factor is λ = 2. We have presented MOSFET's characteristics such as I-V characteristic, impart ionization, electric field, using the TCAD. We have analyzed the adaptive channel and doping influences