• 지식경영연구
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• 제7권2호
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• pp.35-52
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• 2006

Increasing competitive pressure, the constantly accelerating transformation of the economy, and a stronger focus on value creation have initiated the search for sustainable sources of competitive advantage in organizations. In this context, the concept of treating organizational knowledge as a valuable strategic resource has become quite popular recently. Knowledge has become the most critical component in the struggle for sustained competitive advantage and knowledge management (KM) has also been described for its possible role in creating sustainable competitive advantage. In order to examine the contingency between KM resources, KM strategies, and KM performance of organizations, a contingency model of KM, which is based on resource-based theory as well as knowledge-based theory, is developed from the information systems and strategic management literature in order to assess the following questions: (i) What KM resources affect the organization's KM strategies? (ii) Is there a relationship between KM strategies and organizational performance enhanced by KM? A detailed exploratory analysis of survey responses from 79 Korean companies provides the following significant findings: (i) This study found support for the proposed contingency model of KM; (ii) The organization's KM strategies are determined by social resources and its capabilities; (iii) An organization with a culture-based KM strategy is more likely to enhance organizational KM performance than an organization with a technology-based KM strategy.

• Asian-Australasian Journal of Animal Sciences
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• 제19권4호
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• pp.587-592
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• 2006

This study was conducted to evaluate the effects of supplementation with bacillus-based probiotic (Bacillus subtilis, $1.0{\times}10^7CFU/g$; Bacillus coagulans, $2.0{\times}10^6CFU/g$ and Lactobacillus acidophilus, $5.0{\times}10^6CFU/g$) on finishing pigs growth performance, nutrients digestibility, blood characteristics and fecal noxious gas content and to determine the optimal addition level of this probiotic preparation. A total of forty eight pigs with an initial body weight (BW) of $90.60{\pm}2.94kg$ were allotted to three dietary treatments (four pigs per pen with four pens per treatment) according to a randomized complete block design. Dietary treatment included: 1) CON (basal diet); 2) BP1 (basal diet+bacillus-based probiotic 0.1%) and 3) BP2 (basal diet+bacillus-based probiotic 0.2%). The experiment lasted 6 weeks. Through the entire experimental period, ADG was improved by 11% (p<0.05) in pigs fed diets supplemented with 0.2% bacillus-based probiotic compared to pigs fed the basal diet. ADFI and gain/feed were not affected by the treatments (p>0.05). Supplementation of bacillus-based probiotic did not affect either DM and N digestibilities or blood characteristics (p>0.05) of pigs. Fecal ammonia nitrogen ($NH_3$-N) measured at the end of experiment was reduced (p<0.05) when pigs were fed the diet with 0.2% bacillus-based probiotic. Fecal butyric acid concentration also decreased significantly (p<0.05) whereas acetic acid and propionic acid concentrations were not affected (p>0.05) when pigs were fed diets with added bacillus-based probiotic. In conclusion, dietary supplementation of bacillus-based probiotic can increase growth performance and decrease fecal noxious gas content concentration.

• 대한산업공학회지
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• 제37권4호
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• pp.408-414
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• 2011

The objective of this paper is to define local optimization algorithms (LOA) to solve Resource-Constrained Project Scheduling Problem (RCPSP) and analyze the performance of these algorithms. By representing solutions with activity list, three primitive LOAs, i.e. forward and backward improvement-based, exchange-based, and relocation-based LOAs are defined. Also, combined LOAs integrating two primitive LOAs are developed. From the experiments with standard test set J120 generated using ProGen, the FBI-based LOA demonstrates to be an efficient algorithm. Moreover, algorithms combined with FBI-based LOA and other LOA generate good solutions in general. Among the considered algorithms, the combined algorithm of FBI-based and exchangebased shows best performance in terms of solution quality and computation time.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제12권5호
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• pp.275-285
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• 2006

본 논문에서는 그리드 컴퓨팅의 기존 자원 거래망 모델들의 문제점을 분석하고, 해결하기 위한 새로운 자원 거래 모델을 제안한다. 이 모델은 사용자와 자원 공급자 사이의 거래 가격을 예측하고 합리적인 거래 가격을 제시한다. 합리적인 가격 제안을 통해, 사용자와 자원 공급자 사이의 더 많은 자원 거래를 발생시키고, 사용자는 더 짧은 시간에 자원을 공급받게 된다. 본 논문에서 사용자의 자원 요구량 예측 정확도를 향상시키기 위하여 통계학의 예측 모델을 도입하였고 합리적인 가격 제안을 위해 미시 경제학의 가격 결정 이론을 도입하였다. 본 모델의 성능 평가를 위하여 사용자의 자원 요구량 예측 정확도, 자원 거래를 위한 응답시간, 자원 거래 횟수 그리고 사용자의 자원 활용률을 측정하였다. 실험의 결과로는 자원 예측 정확도는 87.45%의 신뢰성 있는 결과를 얻었고, 기존 모델들에 비해 응답시간은 72.39% 단축 되었다. 또한, 자원 거래 횟수는 162.56% 증가 하였다. 본 논문에서 제안하는 모델의 평균 자원 활용률은 90%에 근접했으며 기존 모델들과 비교해서는 230%이상 자원 활용률이 증가 하였다.

• 정보화연구
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• 제10권1호
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• pp.13-22
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• 2013

The Internet has motivated firms to participate in electronic commerce. With the development of electronic commerce, SMEs (small- and medium-sized enterprises) may be forced to use e-intermediaries in export marketing. This study aims at assessing e-intermediaries in various aspects. Empirical and theoretical studies are conducted to investigate determinants and effects of eintermediary use in export marketing. Based on resource-based view (RBV), the study develops a conceptual model that can address the question of which international competence and export performance are closely related to e-intermediary use by SMEs. Based on literature review and theoretical foundations, this study made four hypotheses. With AMOS, structural equation modeling (SEM) was used for testing four hypotheses. The empirical findings support all hypotheses. Last, this study suggests examining comprehensive internal and external factors in terms of e-intermediary use as an interesting topic for future research.

• Journal of information and communication convergence engineering
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• 제15권1호
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• pp.28-36
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• 2017

The medium access control (MAC) protocol based on dynamic time division multiple access/time division duplex (TDMA/TDD) is responsible for random access control and radio resource allocation in dynamic traffic environments. These functions of random access and resource allocation are very important to prevent wastage of resources and improve MAC performance according to various network conditions. In this paper, we propose new random access and resource allocation schemes to guarantee quality of service (QoS) and provide priority services in a dynamic TDMA/TDD system. First, for the QoS guarantee, we propose an adaptive random access and resource allocation scheme by introducing an access probability. Second, for providing priority service, we propose a priority-based random access and resource allocation scheme by extending the first adaptive scheme in both a centralized and a distributed manner. The analysis and simulation results show that the proposed MAC protocol outperforms the legacy MAC protocol using a simple binary exponential backoff algorithm, and provides good differential performance according to priorities with respect to the throughput and delay.

• 한국병원경영학회지
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• 제21권3호
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• pp.53-64
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• 2016

The study empirically examines the classic hypothesis on resource-based view(RBV) theory, which is the possible relationship between competitive advantage and performance. For the study, we have surveyed 198 hospital administrators in Korea. By testing the hypotheses at conceptual level, a more robust approach, we found that (1) if a hospital possesses and exploits resources and capabilities that are both valuable and rare, it will attain a competitive advantage, and (2) the attaintment of such advantage will enable the hospital to improve its performance. The results may be interest to both academics and practitioners. From an academic standpoint, the study more accurately captures the dynamics of the theory by pairing resources-capabilities as opposed to individual resources or capabilities. From a practitioner perspective, it is suggested that hospital managers need no necessarily seek out novel resources and capabilities, but rather develop novel ways in which to combine those resources and capabilities to which they do have access.

• 한국산업정보학회논문지
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• 제8권3호
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• pp.19-31
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• 2003

대규모 환경의 고성능 그리드 구현을 위해서는 기존 그리드 자원 스케줄링 파라다임이 갖 성능 확장성 측면의 제한성을 극복할 수 있는 새로운 자원 스케줄링 프레임워크가 요구된다. 본 연구에서는 자원 스케줄링 성능 최적화를 목표로 자원인자 그래프(Resource Parameter Graph), 자원인자 인덱스 트리(Resource Parameter Index Tree), 그리고 정적 자원 정보 리포지터리로 구성되는 자원인자 스케줄링 프레임워크를 제안한다. 자원인자 그래프는 자원간의 관계 및 자원의 계층적 구성을 나타낼 수 있는 자원표현기법이며 이러한 표현을 기술하기 위한 XML 기반 자원정보 및 자원요청 기술 스키마를 설계하였다. 또한 자원인자 인덱스 트리는 자원 스케줄링의 자원탐색 및 자원할당, 상태정보 공지 등의 알고리즘의 효율적인 지원을 위한 메모리 기반 인덱스의 데이터 구조이다. 본 논문에서는 이러한 자원인자 스케줄링 프레임워크의 구성 내용에 대하여 기술한다.

• 한국통신학회논문지
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• 제34권5A호
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• pp.414-420
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• 2009

본 논문에서는 OFDMA 기반 relay 시스템에서 throughput 성능개선을 위한, Base Station (BS)과 Relay Station (RS)의 sub-cell 커버리지 설정기법을 제안한다. Relay 시스템에서는 BS-RS 링크에서 무선 자원을 추가로 소비하므로, RS간 자원의 재사용을 고려하면 자원의 효과적 사용이 가능하다. 그러나, 이때 신호의 간섭이 증가하므로 단말기의 수신 Signal to Interference and Noise Ratio (SINR)에 영향을 미치게 된다. 그리므로 본 연구에서는 자원 재사용 정도에 따른 사용가능 자원의 증가를 수신 SINR과 함께 sub-cell 커버리지 결정의 요인으로 함께 고려한다. 모의실험을 통한 결과분석을 통해 throughput 성능을 개선할 수 있는 sub-cell 커버리지를, 다양한 자원재사용 패턴에 따라 도출하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권10호
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• pp.1712-1732
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• 2011

Cloud provides dynamically scalable virtualized computing resources as a service over the Internet. To achieve higher resource utilization over virtualization technology, an optimized strategy that deploys virtual machines on physical machines is needed. That is, the total number of active physical host nodes should be dynamically changed to correspond to their resource usage rate, thereby maintaining optimum utilization of physical machines. In this paper, we propose a pattern-based prediction model for resource provisioning which facilitates best possible resource preparation by analyzing the resource utilization and deriving resource usage patterns. The focus of our work is on predicting future resource requests by optimized dynamic resource management strategy that is applied to a virtualized data center in a Cloud computing environment. To this end, we build a prediction model that is based on user request patterns and make a prediction of system behavior for the near future. As a result, this model can save time for predicting the needed resource amount and reduce the possibility of resource overuse. In addition, we studied the performance of our proposed model comparing with conventional resource provisioning models under various Cloud execution conditions. The experimental results showed that our pattern-based prediction model gives significant benefits over conventional models.