• Bulletin of the Korean Chemical Society
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• v.34 no.8
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• pp.2305-2310
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• 2013

A novel series of 2-heteroaryl substituted benzimidazole derivatives, containing the piperidinylphenyl acetamide group at the 1-position, were synthesized and evaluated as MCH-R1 antagonists. Extensive SAR investigation probing the effects of C-2 heteroaryl group led to the identification of 2-[2-(pyridin-3-yl)ethyl] analog 3o, which exhibits highly potent MCH-R1 binding activity with an $IC_{50}$ value of 1 nM. This substance 3o also has low hERG binding activity, good metabolic stability, and favorable pharmacokinetic properties.

• Genomics & Informatics
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• v.17 no.2
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• pp.18.1-18.10
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• 2019

Prediction of the relations among drug and other molecular or social entities is the main knowledge discovery pattern for the purpose of drug-related knowledge discovery. Computational approaches have combined the information from different sources and levels for drug-related knowledge discovery, which provides a sophisticated comprehension of the relationship among drugs, targets, diseases, and targeted genes, at the molecular level, or relationships among drugs, usage, side effect, safety, and user preference, at a social level. In this research, previous work from the BioNLP community and matrix or matrix decomposition was reviewed, compared, and concluded, and eventually, the BioNLP open-shared task was introduced as a promising case study representing this area.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.599-602
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• 2013

e-Discovery 솔루션들의 성능 평가는 일반적으로 증거 확보의 측면에서 강조 되고 있으나, 소송 진행을 위해 추가적으로 제공 되어야 할 기능적인 요소들이 많다는 의견이 제기되며, 평가 기준의 확장 및 측정 할 수 있는 척도의 다양성이 요구 되고 있는 상황이다. 따라서 본 논문에서는 기존 e-Discovery 솔루션의 핵심이라 할 수 있는 증거 검색 기능 및 다양한 업무 절차에서 필수적으로 요구되는 외부적 요인을 결합하여, 객관적이며 신뢰성 있는 e-Discovery 솔루션의 성능 평가를 위한 절차를 제안한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.537-538
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• 2009

IPv6 is newly introduced to solve limitations and problems of IPv4 and in IPv6 network, nodes use Neighbor Discovery protocol to discover the subnet prefix and configure its own address. However, Neighbor Discovery is vulnerable to various attacks as it does not have secure mechanism to protect itself. Thus, the Secure Neighbor Discovery has introduced and the main mechanism used in Secure Neighbor Discovery is Cryptographically Generated Address. In this paper, we provide a brief of Cryptographically Generated Address and its limitation in a case where a mobile node moves from one network to another frequently. The proposed scheme resolves this limitation by using the fixed interface identifier.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.104-106
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• 2023

The mobile crowdsensing platform obtains sensing data from mobile users, and the involvement of the public increases the untrustworthy of collected data. In order to distinguish factual data from inaccurate data provided by untrustworthy users, the truth discovery method has been introduced for accurate data aggregation in mobile crowdsensing (MCS). To explore the application of truth discovery in mobile crowdsensing, we overview the general concepts of truth discovery algorithms. Finally, we summarize the main existing application prospects of truth discovery in mobile crowdsensing.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.2
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• pp.123-128
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• 2009

In ubiquitous computing environments, service discovery to search for an available service is an important issue. In this paper, we propose an efficient service discovery scheme that is combined a node id-based clustering service discovery scheme and a P2P caching-based information spreading scheme. To search quickly a service, proposed scheme store key information in neighbor's local cache and search services using it's information. We do not use a central look up server and do not rely on flooding. Through simulation, we show that the proposed scheme improves the performance of response time and network load compared to other methods.

• English Language & Literature Teaching
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• v.17 no.3
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• pp.27-56
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• 2011

The analysis on the use of lexical discovery and consolidation strategies that have been researched within the area of vocabulary learning strategies (VLS) have not sufficiently drawn the interest of EFL practitioners with regard to vocational high school learners. The results, however, are expected to have implications for the design of vocabulary tasks and instructional materials for EFL learners. The present study investigates EFL vocational high school learners' use of lexical discovery and consolidation strategies with questionnaires, where the use of the learners' lexical discovery strategies were further validated with the think-aloud methodology by asking samples of proficient and less proficient learners to report on their reading process while reading L2 texts that had not been exposed to the learners. The results indicated that there were significant differences between the two groups of learners in the employment of 11 of the strategies which were in the categories of determination, social, memory, and metacognitive strategies, but not for cognitive strategies. The pattern of strategies indicated that different lexical discovery and consolidation strategies were employed relatively more by one proficiency group than another. The study suggests some implications for how strategy-based instruction can be implemented in EFL classrooms.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.278-282
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• 2001

The discovery of tacit knowledge from domain experts is one of the most exciting challenges in today\`s knowledge management. The nature of decision knowledge in determining the quality a firm\`s short-term liquidity is full of abstraction, ambiguity, and incompleteness, and presents a typical tacit knowledge extraction problem. In dealing with knowledge discovery of this nature, we propose a scheme that integrates both knowledge elicitation and knowledge discovery in the knowledge engineering processes. The knowledge elicitation component applies the Verbal Protocol Analysis to establish industrial cases as the basic knowledge data set. The knowledge discovery component then applies fuzzy clustering to the data set to build a fuzzy knowledge based system, which consists of a set of fuzzy rules representing the decision knowledge, and membership functions of each decision factor for verifying linguistic expression in the rules. The experimental results confirm that the proposed scheme can effectively discover the expert\`s tacit knowledge, and works as a feedback mechanism for human experts to fine-tune the conversion processes of converting tacit knowledge into implicit knowledge.

• Journal of information and communication convergence engineering
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• v.6 no.4
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• pp.396-404
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• 2008

Service discovery is the technology of finding needed services in networks, and a key point in pervasive computing environments. This paper presents a novel service discovery protocol: ASESDP(AIP and SRR Enhanced Service Discovery Protocol). In ASESDP, tow schemes are proposed to enhance its performance: AIP(Advertisement Information Piggybacked) and SRR(Shortest Reply Route). In AIP, parts of advertisement information are piggybacked in the service reply packet, which makes the advertisement information propagating along the reply path, and spreads its transmission area. In SRR, in order to reduce the service response time, the shortest reply route is chosen to forward the service reply packet to the source node sending the service request. With the theoretical analysis and Glomosim simulation results, it is verified that ASESDP can reduce the number of service request packets, save the response time, and improve the efficiency of service discovery.

• The Plant Pathology Journal
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• v.33 no.6
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• pp.529-542
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• 2017

Control of plant diseases is largely dependent on use of agrochemicals. However, there are widening gaps between our knowledge on plant diseases gained from genetic/mechanistic studies and rapid translation of the knowledge into target-oriented development of effective agrochemicals. Here we propose that the time is ripe for computer-aided drug discovery/design (CADD) in molecular plant pathology. CADD has played a pivotal role in development of medically important molecules over the last three decades. Now, explosive increase in information on genome sequences and three dimensional structures of biological molecules, in combination with advances in computational and informational technologies, opens up exciting possibilities for application of CADD in discovery and development of agrochemicals. In this review, we outline two categories of the drug discovery strategies: structure- and ligand-based CADD, and relevant computational approaches that are being employed in modern drug discovery. In order to help readers to dive into CADD, we explain concepts of homology modelling, molecular docking, virtual screening, and de novo ligand design in structure-based CADD, and pharmacophore modelling, ligand-based virtual screening, quantitative structure activity relationship modelling and de novo ligand design for ligand-based CADD. We also provide the important resources available to carry out CADD. Finally, we present a case study showing how CADD approach can be implemented in reality for identification of potent chemical compounds against the important plant pathogens, Pseudomonas syringae and Colletotrichum gloeosporioides.