• Research in Plant Disease
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• v.24 no.2
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• pp.99-112
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• 2018

Certain agrochemicals may be tuned for increased effectiveness when downsized to nanoparticles (NPs), where one dimension is less than 100 nm. The NPs may function as fertilizers, pesticides and products to improve plant health through seed priming, growth promotion, and induction of systemic tolerance to stress. Formulations will allow targeted applications with timed release, reducing waste and pollution when compared to treatments with bulk-size products. The NPs may be a single component, such as nano-ZnO as a fertilizer, or be composites of compatible materials, for example where N, P, and K plus micronutrients are available. The active materials could be loaded into porous carriers or tethered to base nanostructures. Coatings could include such natural products alginate, chitosan, zein, or silica. Certain NPs are taken up and transported in the plant's phloem and xylem so systemic effects are feasible. Timed and targeted release of the active product could be achieved in response to changes in pH or availability of ligands within the plant or the rhizosphere. Global research has revealed the many potentials offered by NP formulations to aid sustainability in agriculture. Current work will provide information needed by regulatory agencies to assess their safety in the agricultural setting.

• The Plant Pathology Journal
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• v.30 no.2
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• pp.220-227
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• 2014

The GacS/GacA system in the root colonizer Pseudomonas chlororaphis O6 is a key regulator of many traits relevant to the biocontrol function of this bacterium. Proteomic analysis revealed 12 proteins were down-regulated in a gacS mutant of P. chlororaphis O6. These GacS-regulated proteins functioned in combating oxidative stress, cell signaling, biosynthesis of secondary metabolism, and secretion. The extent of regulation was shown by real-time RT-PCR to vary between the genes. Mutants of P. chlororaphis O6 were generated in two GacS-regulated genes, trpE, encoding a protein involved in tryptophan synthesis, and prnA, required for conversion of tryptophan to the antimicrobial compound, pyrrolitrin. Failure of the trpE mutant to induce systemic resistance in tobacco against a foliar pathogen causing soft rot, Pectobacterium carotovorum SCCI, correlated with reduced colonization of root surfaces implying an inadequate supply of tryptophan to support growth. Although colonization was not affected by mutation in the prnA gene, induction of systemic resistance was reduced, suggesting that pyrrolnitrin was an activator of plant resistance as well as an antifungal agent. Study of mutants in the other GacS-regulated proteins will indicate further the features required for biocontrol-activity in this rhizobacterium.

• Fire Science and Engineering
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• v.15 no.2
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• pp.20-30
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• 2001

The science and technology of seismic hazard mitigation are increasingly being shared among scientists and policy makers around the world. Administrative expertise is also being shared. While there is still tremendous unevenness in technical and administrative capacities and resources, a global community of emergency managers is developing and there is a globalization of expertise. Hazards are better understood, tools for risk assessment are improving, techniques for hazard mitigation are being perfected, and communities and states are implementing more comprehensive disaster preparedness, response, and recovery programs. Priorities are also emerging and hazard mitigation has emerged as the priority of choice in North America and Europe. An increasingly important component of hazard mitigation is resilience, in terms of increased capacities for disaster mitigation and recovery at the community and even individual levels. Each year, more is known about the locations and natures of seismic hazards, although there are still unknown and poorly understood fault lines and limited understanding of related disasters such as tsunamis and landslides. More is known about the impact of earthquakes on the built environment, although nature still provides surprises to confound man's best extorts to reduce risk. More is known about human nature and how people respond to uncertain risk and when confronted by certain catastrophe. However, despite the increased understanding of seismic phenomena and how to protect people and property, there is much that needs to be done to reduce the risk, particularly in major metropolitan areas.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.8
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• pp.8-17
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• 2005

It is well known that preconditioning methods are efficient for convergence acceleration in the compressible low Mach number flows. In this study, the original Euler equations and three differently nondimensionalized preconditioning methods are implemented in two dimensional inviscid bump flows using the 3rd order MUSCL and DADI schemes as numerical flux discretization and time integration, respectively. The multigrid and local time stepping methods are also used to accelerate the convergence. The test case indicates that a properly modified local preconditioning technique involving concepts of a global preconditioning allows Mach number independent convergence. Besides, an asymptotic analysis for properties of preconditioning methods is added.

• Journal of Internet Computing and Services
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• v.2 no.2
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• pp.65-70
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• 2001

In this paper, a Modified RED algorithm for congestion avoidance in IP networks is presented. The RED detects incipient congestion by computing the average queue size. By notifying only a randomly selected fraction of connection, it causes to the global synchronization or fairness problem, And also, the network characteristics need to be known in order to find th optimum average queue length. When the average queue size exceeds a minimum threshold, a modified RED algorithm drops packets based on the state of each connection. Performance is improved because of keeping the average queue size low while allowing occasional bursts of packets in the queue, we compare performance of modified RED with RED and Drop Tail in terms of goodput, network utilization and fairness.

• Journal of Internet Computing and Services
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• v.19 no.2
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• pp.89-98
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• 2018

Media industry is attempting various types of strategic innovation in the content and organization as they enter transition period. However, previous research has casually treated the organizational culture from the management and realized that cognitive/cultural differences between the specific departments yield conflicts. This means the researchers explored less on the decision-making process with the conflict between sub-groups and constituent in the organization. Our study reviewed the most positive method to achieve the innovation outcome through the conflict management within the organization based on the behavioral theory of the firm and applied computer simulation model for analysis to construct the quantitative scenario and infer the result. Conflict always found while media organization experiences innovation within the groups. However, in the long term, securing the independence through the certain state of 'anarchy' which possibly lead consensus implies significance rather to comprise collegiate system for unilateral control. In specific, this study explored the issues in 'conflict management' that has been evaded in media organization research through NK simulation model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.9
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• pp.4438-4460
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• 2017

The Kernelized Correlation Filters (KCF) tracker has caused the extensive concern in recent years because of the high efficiency. Numerous improvements have been made successively. However, due to the abrupt motion between the consecutive image frames, these methods cannot track object well. To cope with the problem, we propose an extended KCF tracker based on swarm intelligence method. Unlike existing KCF-based trackers, we firstly introduce a swarm-based sampling method to KCF tracker and design a unified framework to track smooth or abrupt motion simultaneously. Secondly, we propose a global motion estimation method, where the exploration factor is constructed to search the whole state space so as to adapt abrupt motion. Finally, we give an adaptive threshold in light of confidence map, which ensures the accuracy of the motion estimation strategy. Extensive experimental results in both quantitative and qualitative measures demonstrate the effectiveness of our proposed method in tracking abrupt motion.

• Proceeding of EDISON Challenge
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• 2014.03a
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• pp.1-13
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• 2014

Potential Energy Surface(PES)를 양자 계산을 통해 알아내는 것은 화학 반응을 이해하는 데에 큰 도움이 된다. 이를테면 Transition State(TS)의 configuration을 알 수 있고, 따라서 reaction path와 활성화 에너지 값을 예측하여, 진행시키고자 하는 화학반응의 이해를 도울 수 있다. 하지만 PES를 그리기 위해서는 해당 분자의 다양한 configuration에 대한 singlet point energy 계산이 필요하기 때문에, 계산적인 측면에서 많은 비용을 요구한다. 따라서 product와 reactant의 구조와 같은 critical point의 정보를 이용하여 최소한의 configuration을 sampling하여 전체 PES를 재구성하는 기계학습 알고리즘을 개발하여 다차원 PES 상에서의 화학반응의 예측을 가능하게 하고자 한다. 본 연구에서는 Barbaralane의 두 안정화 된 구조의 critical point로 하여 이 주변을 random normal distribution하여, B3LYP/6-31G(d) level의 DFT 계산을 통해 relaxed scanning하여 구조와 에너지를 구하였으며, 이 정보를 Support Vector Regression(SVR) 알고리즘을 적용하여 PES를 재구현하였으며, 반응경로와 TS의 구조 그리고 활성화 에너지를 구하였다. 또한 본 기계학습 알고리즘을 바닥상태에서 일어나는 반응이 아닌, 들뜬 상태와 전자 구조가 변하는 화학반응, avoid crossing, conical intersection과 같은 Non-adiabatic frame에서 일어나는 현상에 적용 가능성을 논하고자 한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.837-856
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• 2016

Underwater image enhancement has received considerable attention in last decades, due to the nature of poor visibility and low contrast of underwater images. In this paper, we propose a new automatic underwater image enhancement algorithm, which combines nonsubsampled contourlet transform (NSCT) domain enhancement techniques with the mechanism of the human visual system (HVS). We apply the multiscale retinex algorithm based on the HVS into NSCT domain in order to eliminate the non-uniform illumination, and adopt the threshold denoising technique to suppress underwater noise. Our proposed algorithm incorporates the luminance masking and contrast masking characteristics of the HVS into NSCT domain to yield the new HVS-based NSCT. Moreover, we define two nonlinear mapping functions. The first one is used to manipulate the HVS-based NSCT contrast coefficients to enhance the edges. The second one is a gain function which modifies the lowpass subband coefficients to adjust the global dynamic range. As a result, our algorithm can achieve contrast enhancement, image denoising and edge sharpening automatically and simultaneously. Experimental results illustrate that our proposed algorithm has better enhancement performance than state-of-the-art algorithms both in subjective evaluation and quantitative assessment. In addition, our algorithm can automatically achieve underwater image enhancement without any parameter tuning.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3946-3965
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• 2018

Network anomaly detection in Software Defined Networking, especially the detection of DDoS attack, has been given great attention in recent years. It is convenient to build the Traffic Matrix from a global view in SDN. However, the monitoring and management of high-volume feature-rich traffic in large networks brings significant challenges. In this paper, we propose a moving window Principal Components Analysis based anomaly detection and mitigation approach to map data onto a low-dimensional subspace and keep monitoring the network state in real-time. Once the anomaly is detected, the controller will install the defense flow table rules onto the corresponding data plane switches to mitigate the attack. Furthermore, we evaluate our approach with experiments. The Receiver Operating Characteristic curves show that our approach performs well in both detection probability and false alarm probability compared with the entropy-based approach. In addition, the mitigation effect is impressive that our approach can prevent most of the attacking traffic. At last, we evaluate the overhead of the system, including the detection delay and utilization of CPU, which is not excessive. Our anomaly detection approach is lightweight and effective.