• Title/Summary/Keyword: Category Performance

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Implementation of an O-RAN-Compliant Base Station System Using Commercial Off-the-Shelf Components (상용 기성부품을 이용한 O-RAN 호환 기지국 시스템 구현)

  • Du, Hongxin;Zhang, Zhongfeng;Choi, Seungwon;Lee, Taehoon
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.18 no.1
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    • pp.11-24
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    • 2022
  • Open Radio Access Network (O-RAN) standard has been proposed to separate the baseband signal processing unit from the Radio Frequency (RF) unit at base station system mainly for reducing the cost of base station systems through open-source interfaces between the two units. To satisfy the performance metrics in various scenarios, several fronthaul functional split options were presented by O-RAN. Amongst these options, the split option 7-2x is widely adopted in practical applications due to its excellent trade-off between the required bandwidth and RU overhead. In this paper, we present a hardware implementation of a base station system that is compliant with the Category B of O-RAN split option 7-2x. It consists of O-DU and O-RU implemented with a commercial off-the-shelf Digital Signal Processor and RF transceiver, respectively. The performance of the proposed base station system is evaluated in terms of Bit Error Rate and received signal power as well as the required fronthaul bandwidth. Through various experimental tests, we have observed that the proposed system reduces the fronthaul bandwidth nearly by 89.7% compared to the conventional system that dose not employ the O-RAN standard.

A FACETS Analysis of Rater Characteristics and Rater Bias in Measuring L2 Writing Performance

  • Shin, You-Sun
    • English Language & Literature Teaching
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    • v.16 no.1
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    • pp.123-142
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    • 2009
  • The present study used multi-faceted Rasch measurement to explore the characteristics and bias patterns of non-native raters when they scored L2 writing tasks. Three raters scored 254 writing tasks written by Korean university students on two topics adapted from the TOEFL Test of Written English (TWE). The written products were assessed using a five-category rating scale (Content, Organization, Language in Use, Grammar, and Mechanics). The raters only showed a difference in severity with regard to rating categories but not in task types. Overall, the raters scored Grammar most harshly and Organization most leniently. The results also indicated several bias patterns of ratings with regard to the rating categories and task types. In rater-task bias interactions, each rater showed recurring bias patterns in their rating between two writing tasks. Analysis of rater-category bias interaction showed that the three raters revealed biased patterns across all the rating categories though they were relatively consistent in their rating. The study has implications for the importance of rater training and task selection in L2 writing assessment.

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Personalized Information Delivery Methods for Knowledge Portals (지식포탈을 위한 개인화 지식 제공 방안)

  • Lee Hong Joo;Kim Jong Woo;Kim Gwang Rae;Ahn Hyung Jun;Kwon Chul Hyun;Park Sung Joo
    • Journal of Information Technology Applications and Management
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    • v.12 no.4
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    • pp.45-57
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    • 2005
  • In order to provide personalized knowledge recommendation services, most web portals for organizational knowledge management use category or keyword information that portal users explicitly express interests in. However, it is usually difficult to collect correct preference data for all users with this approach, and, moreover, users' preferences may easily change over time, which results In outdated user profiles and impaired recommendation qualify. In order to address this problem, this paper suggests knowledge recommendation methods for portals using user profiles that are automatically constructed from users' activities such as posting or uploading of articles and documents. The result of our experiment shows that the Proposed method can provide equivalent performance with the manual category or keyword selection method.

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A Empirical Study on the Development of Quality Management used MB Model in Public Sector: Focused on Autonomy Administration (공공부문에서 MB모형을 이용한 품질경영 인과모형의 구축에 관한 탐색적인 연구: 자치행정부문을 중심으로)

  • 김계수
    • Journal of the Korean Operations Research and Management Science Society
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    • v.27 no.3
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    • pp.41-57
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    • 2002
  • In this paper, I investigate the impact of quality management activities on the public sector within the framework of Malcolm Baldrige (MB) national qualify model. The Structural Equation Modeling approach has been employed to investigate the cross influences among the seven MB categories. This empirical study shows that a number of statistical hypotheses are significant. The leadership category is the most important driver among the quality management activities. This, in turn, implies that the main source in quality management is to foster a solid qualify oriented leadership system. Categories such as Information Analysis, Strategic Planning, Human Resource Development and Management, and Process Management are significantly related to the Customer Satisfaction category. In addition, leadership, Information Analysis, and Customer Satisfaction categories ere significantly influential to Management Performance.

Quantized DCT Coefficient Category Address Encryption for JPEG Image

  • Li, Shanshan;Zhang, Yuanyuan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.4
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    • pp.1790-1806
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    • 2016
  • Digital image encryption is widely used for image data security. JPEG standard compresses image with great performance on reducing file size. Thus, to encrypt an image in JPEG format we should keep the quality of original image and reduced size. This paper proposes a JPEG image encryption scheme based on quantized DC and non-zero AC coefficients inner category scrambling. Instead of coefficient value encryption, the address of coefficient is encrypted to get the address of cipher text. Then 8*8 blocks are shuffled. Chaotic iteration is employed to generate chaotic sequences for address scrambling and block shuffling. Analysis of simulation shows the proposed scheme is resistant to common attacks. Moreover, the proposed method keeps the file size of the encrypted image in an acceptable range compared with the plain text. To enlarge the cipher text possible space and improve the resistance to sophisticated attacks, several additional procedures are further developed. Contrast experiments verify these procedures can refine the proposed scheme and achieve significant improvements.

A Three-Step Preprocessing Algorithm for Enhanced Classification of E-Mail Recommendation System (이메일 추천 시스템의 분류 향상을 위한 3단계 전처리 알고리즘)

  • Jeong Ok-Ran;Cho Dong-Sub
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.54 no.4
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    • pp.251-258
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    • 2005
  • Automatic document classification may differ significantly according to the characteristics of documents that are subject to classification, as well as classifier's performance. This research identifies e-mail document's characteristics to apply a three-step preprocessing algorithm that can minimize e-mail document's atypical characteristics. In the first 5go, uncertain based sampling algorithm that used Mean Absolute Deviation(MAD), is used to address the question of selection learning document for the rule generation at the time of classification. In the subsequent stage, Weighted vlaue assigning method by attribute is applied to increase the discriminating capability of the terms that appear on the title on the e-mail document characteristic level. in the third and last stage, accuracy level during classification by each category is increased by using Naive Bayesian Presumptive Algorithm's Dynamic Threshold. And, we implemented an E-Mail Recommendtion System using a three-step preprocessing algorithm the enable users for direct and optimal classification with the recommendation of the applicable category when a mail arrives.

Rule Selection Method in Decision Tree Models (의사결정나무 모델에서의 중요 룰 선택기법)

  • Son, Jieun;Kim, Seoung Bum
    • Journal of Korean Institute of Industrial Engineers
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    • v.40 no.4
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    • pp.375-381
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    • 2014
  • Data mining is a process of discovering useful patterns or information from large amount of data. Decision tree is one of the data mining algorithms that can be used for both classification and prediction and has been widely used for various applications because of its flexibility and interpretability. Decision trees for classification generally generate a number of rules that belong to one of the predefined category and some rules may belong to the same category. In this case, it is necessary to determine the significance of each rule so as to provide the priority of the rule with users. The purpose of this paper is to propose a rule selection method in classification tree models that accommodate the umber of observation, accuracy, and effectiveness in each rule. Our experiments demonstrate that the proposed method produce better performance compared to other existing rule selection methods.

Text Classification Method Using Deep Learning Model Fusion and Its Application

  • Shin, Seong-Yoon;Cho, Gwang-Hyun;Cho, Seung-Pyo;Lee, Hyun-Chang
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2022.10a
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    • pp.409-410
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    • 2022
  • This paper proposes a fusion model based on Long-Short Term Memory networks (LSTM) and CNN deep learning methods, and applied to multi-category news datasets, and achieved good results. Experiments show that the fusion model based on deep learning has greatly improved the precision and accuracy of text sentiment classification. This method will become an important way to optimize the model and improve the performance of the model.

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A Study on the Optimization of New Renewable Energy Systems in Public-Purpose Facilities (공공용 업무시설의 신재생에너지시스템 최적화 연구)

  • Lee, Yong-Ho;Seo, Sang-Hyun;Cho, Young-Hum;Hwang, Jung-Ha
    • Journal of the Korean Solar Energy Society
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    • v.33 no.5
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    • pp.95-104
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    • 2013
  • This study set out to devise an optimized system to take into account life cycle cost(LCC) and ton of carbon dioxide($TCO_2$) by applying the weighted coefficient method(WCM) to "public-purpose" facility buildings according to the mandatory 5% and 11% of new renewable energy in total construction costs and anticipated energy consumption, respectively, based on the changes of the public obligation system. (1) System installation capacity is applied within the same new renewable energy facility investment according to the mandatory 5% of new renewable energy in total construction costs. Both LCC and $TCO_2$ recorded in the descending order of geothermal, solar, and photovoltaic energy. The geothermal energy systems tended to exhibit an excellent performance with the increasing installation capacity percentage. (2) Optimal systems include the geothermal energy(100%) system in the category of single systems, the solar energy(12%)+geothermal energy(88%) system in the category of 2-combined systems, and the photovoltaic energy(12%)+solar energy(12%)+geothermal energy(76%) system and the photovoltaic energy(12%)+solar energy(25%)+geothermal energy(63%) system in the category of 3-combined systems. (3) LCC was the highest in the descending order of photovoltaic, geothermal and solar energy due to the influences of each energy source's correction coefficient according to the mandatory 11% of new renewable energy in anticipated energy consumption. The greater installation capacity percentage photovoltaic energy had, the more excellent tendency was observed. $TCO_2$ recorded in the descending order of geothermal, photovoltaic and solar energy with the decreasing installation capacity of photovoltaic energy. The greater installation capacity percentage a geothermal energy system had, the more excellent tendency it demonstrated. (4) Optimal systems include the geothermal energy(100%) system in the category of single systems, the photovoltaic energy(62%)+geothermal energy(38%) system in the category of 2-combined systems, and the photovoltaic energy(50%)+solar energy(12%)+geothermal energy(38%) system and the photovoltaic energy(12%)+solar energy(12%)+geothermal energy(76%) system in the category of 3-combined systems.

An Exploratory Study on the Performance Indicators for Management that Reveals Creativity (창조성 발현 경영을 위한 성과지표에 대한 탐색적 연구)

  • Oh, Hyung-Sool;Seong, Baek-Seo;Kim, Seon-Min
    • Journal of the Korea Safety Management & Science
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    • v.10 no.2
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    • pp.61-70
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    • 2008
  • The CEOs of global companies have been realized the imagination and creativity that can be obtained from the corporate culture is the crucial competitive power for sustainable growth. Thus, most domestic companies take an increasing interest in how to make creativity efficiently. This paper, however, argues that the proper application of performance indicators can engender creativity and innovation in organizations without costly investing on creativity. Assuming that creativity is actually dominated by the emotion of human resources rather than the rationality, this paper suggests the performance indicators developed based on the viewpoint of the characteristics of human needs and the relationship between the human needs and the attribute of works. The performance system which consists of activity, sociality and creativity is presented and the performance indicators for each category are also suggested to improve the spontaneity and creativity of human resources.