• Title/Summary/Keyword: Discovery Time

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DMRUT-MCDS: Discovery Relationships in the Cyber-Physical Integrated Network

  • Lu, Hongliang;Cao, Jiannong;Zhu, Weiping;Jiao, Xianlong;Lv, Shaohe;Wang, Xiaodong
    • Journal of Communications and Networks
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    • v.17 no.6
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    • pp.558-567
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    • 2015
  • In recent years, we have seen a proliferation of mobile-network-enabled smart objects, such as smart-phones and smart-watches, that form a cyber-physical integrated network to connect the cyber and physical worlds through the capabilities of sensing, communicating, and computing. Discovery of the relationship between smart objects is a critical and nontrivial task in cyber-physical integrated network applications. Aiming to find the most stable relationship in the heterogeneous and dynamic cyber-physical network, we propose a distributed and efficient relationship-discovery algorithm, called dynamically maximizing remaining unchanged time with minimum connected dominant set (DMRUT-MCDS) for constructing a backbone with the smallest scale infrastructure. In our proposed algorithm, the impact of the duration of the relationship is considered in order to balance the size and sustain time of the infrastructure. The performance of our algorithm is studied through extensive simulations and the results show that DMRUT-MCDS performs well in different distribution networks.

Pharmacogenomics in Drug Discovery and Development

  • Ahn, Chul
    • Genomics & Informatics
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    • v.5 no.2
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    • pp.41-45
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    • 2007
  • Pharmacogenomics is the study that examines how genetic variations affect the ways in which people respond to drugs. The ways people respond to drugs are complex traits that are influenced by many different genes. Pharmacogenomics intends to develop rational means of optimizing drug therapy, with respect to the patients' genotype, to maximize efficacy with minimal adverse drug reactions. Pharmacogenomics has the potential to revolutionize the practice of medicine, and promises to usher in an area of personalized medicine, in which drugs and drug combinations are optimized for each individual's unique genetic makeup. Indeed, pharmacogenomics is exploited as an essential step for target discovery and drug development in the pharmaceutical industry. The goal of the personalized medicine is to get the right dose of the right drug to the right patient at the right time. In this article, we will review the use of pharmacogenomics in drug discovery and development.

A Multi-hop routing protocol for bluetooth devices (블루투스 멀티 홉 라우팅 프로토콜)

  • Yang, Il-Sik;Kim, Myung-Gyu;Son, Ji-Yeon;Park, Jun-Seok
    • Proceedings of the KIEE Conference
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    • 2005.10b
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    • pp.448-450
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    • 2005
  • A ubiquitous network allows all users to access and exchange information of any kind freely at any time, from anywhere, and from any appliance through the use of broadband and mobile access. Bluetooth commincation can provide the missing wireless extension to the heterogeneous network, allowing a more ubiquitous access. In this point of view, the BT specifications define ways for which each BT device can set up multiple connections with neighboring devices to communicate in a multi-hop fashion. this paper provides insights on the Bluetooth technology and on some limitations of the scatternet formations. so that, we describe a new multi-hop routing protocol for the establishment of scatternets. this protocol defines rules for forming a multi-hop topology in two phases. the first phase, topology discovery, concerns the discovery of the node's depth from a root node initiating inquiry process. the second phase forms scatternet topology based on the result of topology discovery.

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Evaluation of Advanced Structure-Based Virtual Screening Methods for Computer-Aided Drug Discovery

  • Lee, Hui-Sun;Choi, Ji-Won;Yoon, Suk-Joon
    • Genomics & Informatics
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    • v.5 no.1
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    • pp.24-29
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    • 2007
  • Computational virtual screening has become an essential platform of drug discovery for the efficient identification of active candidates. Moleculardocking, a key technology of receptor-centric virtual screening, is commonly used to predict the binding affinities of chemical compounds on target receptors. Despite the advancement and extensive application of these methods, substantial improvement is still required to increase their accuracy and time-efficiency. Here, we evaluate several advanced structure-based virtual screening approaches for elucidating the rank-order activity of chemical libraries, and the quantitative structureactivity relationship (QSAR). Our results show that the ensemble-average free energy estimation, including implicit solvation energy terms, significantly improves the hit enrichment of the virtual screening. We also demonstrate that the assignment of quantum mechanical-polarized (QM-polarized) partial charges to docked ligands contributes to the reproduction of the crystal pose of ligands in the docking and scoring procedure.

Tutorial on Drug Development for Central Nervous System

  • Yoon, Hye-Jin;Kim, Jung-Su
    • Interdisciplinary Bio Central
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    • v.2 no.4
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    • pp.9.1-9.5
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    • 2010
  • Many neurodegenerative diseases, such as Alzheimer's and Parkinson's disease, are devastating disorders that affect millions of people worldwide. However, the number of therapeutic options remains severely limited with only symptomatic management therapies available. With the better understanding of the pathogenesis of neurodegenerative diseases, discovery efforts for disease-modifying drugs have increased dramatically in recent years. However, the process of translating basic science discovery into novel therapies is still lagging behind for various reasons. The task of finding new effective drugs targeting central nervous system (CNS) has unique challenges due to blood-brain barrier (BBB). Furthermore, the relatively slow progress of neurodegenerative disorders create another level of difficulty, as clinical trials must be carried out for an extended period of time. This review is intended to provide molecular and cell biologists with working knowledge and resources on CNS drug discovery and development.

Organizational Capabilities for Effective Knowledge Creation: An In-depth Case Analysis of Quinolone Antibacterial Drug Discovery Process (효과적 지식창출을 위한 조직능력 요건: 퀴놀론계 항생제 개발 사례를 중심으로)

  • Lee, Chun-Keun;Kim, Linsu
    • Knowledge Management Research
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    • v.2 no.1
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    • pp.109-132
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    • 2001
  • The purpose of this article is to develop a dynamic model of organizational capabilities and knowledge creation, and at the same time identify the organizational capability factors for effective knowledge creation, by empirically analyzing the history of new Quinolone antibacterial drug compound (LB20304a) discovery process at LG, as a case in point. Major findings of this study are as follows. First, in a science-based area such as drug development, the core of successful knowledge creation lies in creative combination of different bodies of scientific explicit knowledge. Second, the greater the difficulty of learning external knowledge, the more tacit knowledge is needed for the recipient firm to effectively exploit that knowledge. Third, in science-based sector such as pharmaceutical industry, the key for successful knowledge creation lies in the capability of recruiting and retaining star scientists. Finally, for effective knowledge creation, a firm must keep its balance among three dimensions of organizational capabilities: local, process, architectural capabilities.

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The HCARD Model using an Agent for Knowledge Discovery

  • Gerardo Bobby D.;Lee Jae-Wan;Joo Su-Chong
    • The Journal of Information Systems
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    • v.14 no.3
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    • pp.53-58
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    • 2005
  • In this study, we will employ a multi-agent for the search and extraction of data in a distributed environment. We will use an Integrator Agent in the proposed model on the Hierarchical Clustering and Association Rule Discovery(HCARD). The HCARD will address the inadequacy of other data mining tools in processing performance and efficiency when use for knowledge discovery. The Integrator Agent was developed based on CORBA architecture for search and extraction of data from heterogeneous servers in the distributed environment. Our experiment shows that the HCARD generated essential association rules which can be practically explained for decision making purposes. Shorter processing time had been noted in computing for clusters using the HCARD and implying ideal processing period than computing the rules without HCARD.

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Unrecorded species of Korean protozoans discovered through the project of 'Discovery of Korean Indigenous Species' III

  • Kyu-Seok Chae;Kang-San Kim;Jongwoo Jung;Gi-Sik Min
    • Journal of Species Research
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    • v.12 no.4
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    • pp.355-361
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    • 2023
  • In this paper, we present unrecorded protozoans of Korea that were discovered, through the 'Discovery of Korean Indigenous Species' project hosted by the 'National Institute of Biological Resources (NIBR)'. A taxonomic account is provided for each identified species, offering comprehensive information such as species name, Korean name, collection site, synonyms, specimen vouchers, diagnoses, and figures. This study introduces 13 previously unrecorded Korean protozoan species that are classified into three phyla: Amoebozoa, Cercozoa, and Ciliophora. Notably, the cercozoan family Chlamydophryidae was recorded in Korea for the first time, together with the discovery of three previously unreported genera: Diaphoropodon within Cercozoa, and Metauroleptus and Hemicycliostyla within Ciliophora.

A Study on Price Discovery and Interactions Among Natural Gas Spot Markets in North America (북미 천연가스 현물시장간의 가격발견과 동태적 상호의존성에 대한 연구)

  • Park, Haesun
    • Environmental and Resource Economics Review
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    • v.15 no.5
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    • pp.799-826
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    • 2006
  • Combining recent advances in causal flows with time series analysis, relationships among eight North American natural gas spot market prices are examined. Results indicate that price discovery tends to occur in excess demand regions and move to excess supply regions. Across North America, the U.S. Midwest region represented by Chicago spot market is the most important market for price discovery. The Ellisburg-Leidy Hub in Pennsylvania is important in price discovery, especially for markets in the eastern two-thirds of the U.S. Malin Hub in Oregon is important for the western markets including the AECO Hub in Alberta, Canada.

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