• The Journal of the Korea Contents Association
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• v.12 no.5
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• pp.470-477
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• 2012

Climate related policies have been considered due to increase of energy and fossil fuel consumption. Therefore, research has been done to reduce $CO_2$ and to implement green construction. This paper proposes green construction performance metrics for transportation facilities based on previous literature review and survey. The metrics are composed with economic, social, and environment parts and number of metrics are 14, 10, and 12 respectively. The survey was performed to evaluate relevance, clarity, timeliness, comparable, and obtainable of the proposed metrics. Then implementation strategy is also proposed for effective use.

• Asia-Pacific Journal of Business
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• v.2 no.2
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• pp.1-35
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• 2011

Facing information overload in today's complex environments, managers look to a concise set of marketing metrics to provide direction for marketing decision making. While there have been several papers dealing with the theoretical aspects of dashboard creation, no research creates and tests a dashboard using scientific techniques. This study develops and demonstrates an empirical approach to dashboard metric selection. In a fast moving consumer goods category, this research selects leading indicators for national-brand and store-brand sales and revenue premium performance from 99 brand-specific and relative-to-competition variables including price, brand equity, usage occasions, and multiple measures of awareness, trial/usage, purchase intent, and liking/satisfaction. Plotting impact size and wear-in time reveals that different kinds of variables predict sales at distinct lead times, which implies that managerial action may be taken to turn the metrics around before performance itself declines.

• Journal of Multimedia Information System
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• v.5 no.4
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• pp.291-297
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• 2018

Performance measurement is not an easy task. However, it is necessary to measure the expected value of the informatization project to be invested, to help the successful progress of the informatization project, and to confirm the result of the informatization project. This study describes the evaluation systems of the defense informatization project in Korea used after the end of the informatization project (post-implementation evaluation stage). In the post-implementation evaluation stage of proposed system, the informatization project is evaluated in terms of performance achievement, project plan compliance, project management, and economic validity. For each element, this study suggests metrics and practical measurement method. With metrics and their method, it can be evaluated which project is better than others. Moreover, the lessons learned can be developed. Under scarce budget condition, defense organizations can make better performance from IT project with the evaluation system suggested in this study.

• Proceedings of the IEEK Conference
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• 2000.11a
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• pp.441-444
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• 2000

This paper covers the performance testing for layer 3 Ethernet switch based on various methodologies by which we can measure essential metrics such as throughput, latency, frame loss rate, and back to back frames. In the first place, layer 2 and layer 3 switch evolution is introduced followed by description of IP packet switching in layer 3 switch. And then, the above test metrics and test methodologies are illustrated as well. At last, we conduct the performance testing for layer 3 switch in case of transmitting packets of 64, 128, 256, 512, 1024, 1280, and 1518 byte size and analyze then results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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• pp.3865-3883
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• 2016

Infrastructure as a Service (IaaS) encapsulates computer hardware into a large amount of virtual and manageable instances mainly in the form of virtual machine (VM), and provides rental service for users. Currently, VM anomaly incidents occasionally occur, which leads to performance issues and even downtime. This paper aims at detecting anomalous VMs based on performance metrics data of VMs. Due to the dynamic nature and increasing scale of IaaS, detecting anomalous VMs from voluminous correlated and non-Gaussian monitored performance data is a challenging task. This paper designs an anomaly detection framework to solve this challenge. First, it collects 53 performance metrics to reflect the running state of each VM. The collected performance metrics are testified not to follow the Gaussian distribution. Then, it employs independent components analysis (ICA) instead of principal component analysis (PCA) to extract independent components from collected non-Gaussian performance metric data. For anomaly detection, it employs multi-class Bayesian classification to determine the current state of each VM. To evaluate the performance of the designed detection framework, four types of anomalies are separately or jointly injected into randomly selected VMs in a campus-wide testbed. The experimental results show that ICA-based detection mechanism outperforms PCA-based and LDA-based detection mechanisms in terms of sensitivity and specificity.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.1019-1022
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• 2012

Integral imaging is a promising technology for 3D imaging and display. Many parameters affect the performance of 3D integral imaging systems. Enhanced system performance is acquired by optimization of these system parameters with respect to defined performance metrics. In this paper, we present an approach to optimize the performance of 3D integral imaging system in terms of performance metrics under fixed resource constraints. In this analysis, system parameters such as lens numerical aperture, pitch between image sensors, the number of image sensors, the pixel size, and the number of pixels are determined to optimize performance metrics. Wave optics is utilized to describe the imaging process.

• STI Policy Review
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• v.9 no.1
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• pp.1-29
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• 2018

With the constant growth of R&D investment, it has been increasingly necessary to evaluate the effectiveness of R&D performance and there is a high emphasis on ensuring the accountability and effectiveness of R&D programs. The evaluation of performance of a firm is especially necessary in times of economic downturn to justify R&D investment. However, there is a marked shortage of clear guidelines as to where and how particular metrics are used to measure the output and outcome of R&D activity in firms. Many firms have difficulties in selecting appropriate indicators for their R&D and financial performances. To fill this gap, this article discusses and presents the findings from the literature in such a way that they become useful for researchers or managers who are in charge of measuring the R&D and business performances arising from innovation activities. Finally, based on the findings about metrics of R&D performance, this article proposes the hypothetical framework to investigate the relationship between technology forecasting, strategic technology planning, and business performance. The framework of this article will assist policy makers, universities, research institutes/national laboratories, and companies to enhance their decision making process in technology development.

• MALSORI
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• no.66
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• pp.41-59
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• 2008

Knowledge in linguistic rhythm of the target language plays a major role in foreign language proficiency. This study attempts to discover valid rhythm features that can be utilized in automatic assessment of non-native English pronunciation. Eight previously proposed and two novel rhythm metrics are investigated with 360 English read speech tokens obtained from 27 Korean learners and 9 native speakers. It is found that some of the speech-rate normalized interval measures and above-word level metrics are effective enough to be further applied for automatic scoring as they are significantly correlated with speakers' proficiency levels. It is also shown that metrics need to be dynamically selected depending upon the structure of target sentences. Results from a preliminary auto-scoring experiment through a Multi Regression analysis suggest that appropriate control of unexpected input utterances is also desirable for better performance.

• Knowledge Management Research
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• v.11 no.4
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• pp.21-39
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• 2010

Recommender system is a core component of e-commerce. Correspondingly, metrics to evaluate the system performance have been developed and applied. However, even though we have lots of applications that have tried to adopt recommender systems, the dearth of successfully installed recommender systems for more than a decade leads us to a skeptical thinking that current metrics do not sufficiently indicate the recommender system success in business viability point of view. Hence, the purpose of this paper is to reconfigure measures for recommender system success. Adopting DeLone and McLean's amended model of information system success as the underlying framework, content analysis with intellectual properties on recommender systems was conducted to modify the currently used metrics. Then a model of recommender system success is proposed based on the newly identified metrics are compared with traditional metrics.

• Journal of the Korean Society for Library and Information Science
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• v.57 no.3
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• pp.249-277
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• 2023

The purpose of this study is to explore the potential contribution of citation metrics to improving the search performance of citation index databases. To this end, the study generated ten queries in the field of library and information science and conducted experiments based on the relevance assessment using 3,467 documents retrieved from the Web of Science and 60,734 documents published in 85 SSCI journals in the field of library and information science from 2000 to 2021. The experiments included re-ranking of the top 100 search results using citation metrics and search methods, query expansion experiments using vector space model retrieval systems, and the construction of a citation-based re-ranking system. The results are as follows: 1) Re-ranking using citation metrics differed from Web of Science's performance, acting as independent metrics. 2) Combining query term frequencies and citation counts positively affected performance. 3) Query expansion generally improved performance compared to the vector space model baseline. 4) User-based query expansion outperformed system-based. 5) Combining citation counts with suitability documents affected ranking within top suitability documents.