• Asian Pacific Journal of Cancer Prevention
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• v.16 no.18
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• pp.8047-8052
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• 2016

Proteases are important molecules that are involved in many key physiological processes. Protease signaling pathways are strictly controlled, and disorders in protease activity can result in pathological changes such as cardiovascular and inflammatory diseases, cancer and neurological disorders. Many proteases have been associated with increasing tumor metastasis in various human cancers, suggesting important functional roles in the metastatic process because of their ability to degrade the extracellular matrix barrier. Proteases are also capable of cleaving non-extracellular matrix molecules. Inhibitors of proteases to some extent can reduce invasion and metastasis of cancer cells, and slow down cancer progression. In this review, we focus on the role of a few proteases and their inhibitors in tumors as a basis for cancer prognostication and therapy.

• The Journal of the Acoustical Society of Korea
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• v.25 no.3E
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• pp.89-94
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• 2006

For audio indexing and targeted search of specific audio or corresponding visual contents, the MPEG-7 standard has adopted a sound classification framework, in which dimension-reduced Audio Spectrum Projection (ASP) features are used to train continuous hidden Markov models (HMMs) for classification of various sounds. The MPEG-7 employs Principal Component Analysis (PCA) or Independent Component Analysis (ICA) for the dimensional reduction. Other well-established techniques include Non-negative Matrix Factorization (NMF), Linear Discriminant Analysis (LDA) and Discrete Cosine Transformation (DCT). In this paper we compare the performance of different dimensional reduction methods with Gaussian mixture models (GMMs) and HMMs in the classifying video sound clips.

• IMMUNE NETWORK
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• v.13 no.3
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• pp.81-85
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• 2013

The mucosal surfaces are constantly exposed to incoming pathogens which can cause infections that result in severe morbidity and/or mortality. Studies have reported that mucosal immunity is important for providing protection against these pathogens and that mucosal vaccination is effective in preventing local infections. For many years, the sublingual mucosa has been targeted to deliver immunotherapy to treat allergic hypersensitivities. However, the potential of vaccine delivery via sublingual mucosal has received little attention until recently. Recent studies exploring such potential have documented the safety and effectiveness of sublingual immunization, demonstrating the ability of sublingual immunization to induce both systemic and mucosal immune responses against a variety of antigens, including soluble proteins, inter particulate antigens, and live-attenuated viruses. This review will summarize the recent findings that address the promising potential of sublingual immunization in proving protection against various mucosal pathogens.

• Proceedings of the Korean Society of Computer Information Conference
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• 2013.07a
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• pp.193-194
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• 2013

사회구조의 발전과 산업의 가속화는 중앙지역과 지역경제의 경계를 더욱 분명하게 만들고 있다. 인구 밀도와 경제규모의 차이가 이를 대변하고 있다고 할 수 있다. 이에 본 연구에서는 대한민국의 중규모 도시에서 마케팅 활성화를 위한 방안으로 여성을 타겟으로 패션 스타킹과 레깅스 등 여성용 제품에 대한 마케팅 전략을 위한 서비스 개발에 관하여 살펴보고자 한다. 이를 통해 지역 경제를 구성하고 있는 주민의 절반인 여성고객을 대상으로 마케팅 활성화를 통한 지역 경제 활성화에 이바지 할 것으로 기대된다.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.10a
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• pp.542-549
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• 2004

The compressive strength of concrete is commonly used criterion in producing concrete. However, the tests on the compressive strength are complicated and time-consuming. More importantly, it is too late to make improvement even if the test result does not satisfy the required strength, since the test is usually performed at the 28th day after the placement of concrete at the construction site. Therefore, accurate and realistic strength estimation before the placement of concrete is being highly required. In this study, the estimation of the compressive strength of concrete was performed by probabilistic neural network (PNN) on the basis of concrete mix proportions. The estimation performance of PNN was improved by considering the correlation between input data and targeted output value. Adaptive probabilistic neural network (APNN) was proposed to automatically calculate the smoothing parameter in the conventional PNN by using the scheme of dynamic decay adjustment algorithm. The conventional PNN and APNN were applied to predict the compressive strength of concrete using actual test data of a concrete company. APNN showed better results than the conventional PNN in predicting the compressive strength of concrete.

• Convergence Security Journal
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• v.7 no.1
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• pp.99-106
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• 2007

We propose a distributed anchor Crossover Switches (CX) searching algorithm to play an important role in ensuring fast and seamless handoff control in wireless ATM networks. Within networks that are grouped together, connection management is done for each group by anchor switches, and Permanent Virtual Circuit (PVC) with a narrow bandwidth is assigned between anchors for exchange of information. The proposed algorithm enables quick searching of a targeted CX, makes management of the overall network easier, and reduces system overhead or propagation delay time, thus providing fast and seamless handoff.

• Convergence Security Journal
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• v.12 no.4
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• pp.97-108
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• 2012

In this study, we analysis the distributing malware using email on the korean defense service and defense industry as the social engineering attack. E-mail attack distributes the document files with the malware. Using the malware, attacker get the Information of the targeted people and devices. we proposed expected new types of attacks by analysis and transformation. And, expect the new email attack agendas which will be tried.

• Progress in Superconductivity and Cryogenics
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• v.15 no.3
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• pp.29-34
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• 2013

This paper introduces design processes of 10 MW class superconducting generator for wind Turbine. Superconducting generator can produce 5 times stronger magnetic field than permanent magnet at least, which enables large scale wind turbine to function as a lighter, smaller and more highly efficient system. These processes are targeted for higher efficiency and shorter high temperature superconductor (HTS) wires to fabricate 10 MW class superconducting generator. Three different approaches will be described in these design processes. First design process focuses on the number of rotor poles. Secondly, 270 and 360 A operating current of superconducting field coil can be adapted as a design parameter in this process. Lastly, 3 and 6 kV line to line voltage of stator coil will be used to design 10 MW class superconducting generator.

• Journal of Environmental Health Sciences
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• v.33 no.5
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• pp.428-433
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• 2007

To clarify the pioneer group in the development of biofilms in high chlorine residual water, a semi-pilot model system was operated and 16S rDNA V3 targeted PCR-DGGE was submitted. Biofilm formation occurred rapidly in the model of a drinking water distribution system. It reached $10^3\;CFU/cm^2$ or more on the surface of stainless steel, PVC, and galvanized iron in chlorinated (1.0 mg/l) water within a week. Within a week, uncultured Proteobacteria- and Bacillales group-like sequences were detected and Sphingomonas-like sequences were identified from all season and all pipe materials tested. Hence Sphingomonas species were regarded as the potential pioneer group in the development of biofilm in drinking water and this results would be useful for the prevention of biofilm formation and safety of drinking tap water.

• The Bulletin of The Korean Astronomical Society
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• v.39 no.2
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• pp.42.1-42.1
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• 2014

Neutrino science has received a boost of attention quite recently in cosmology, since the outstanding discovery in particle physics over the last decade that neutrinos are massive: pinpointing the neutrino masses is one of the greatest challenges in science today, at the cross-road between particle-physics, astrophysics, and cosmology. Cosmology offers a unique 'laboratory' with the best sensitivity to the neutrino mass, as primordial massive neutrinos comprise a small portion of the dark matter and are known to significantly alter structure formation. I will first introduce a new suite of state-of-the-art hydrodynamical simulations with cold dark matter, baryons and massive neutrinos, specifically targeted for modeling the low-density regions of the intergalactic medium as probed by the Lyman-Alpha forest at high-redshift. I will then present and discuss how these simulations are used to constrain the parameters of the LCDM cosmological model in presence of massive neutrinos, in combination with BOSS data and other cosmological probes, leading to the strongest bound to date on the total neutrino mass.