• Title/Summary/Keyword: Big6 model

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Performance analysis ofthe improved reverse link closed loop powercontrol with the variable step size for the mobile transmit power (이동국 가변증감량 조정방법에 의한 역방향 폐쇄회로 전력제어 성능개선 연구)

  • 원석호;정인명;임덕채;김환우
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.21 no.6
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    • pp.1567-1575
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    • 1996
  • This paper presents a new power control method for compensating the short term fading of the reverse link channel in the CDMA mobile telephone system. The fixed step closed loop power control which is now adopted in IS-95, is very simple in structure. However, the step size in the closed loop power control is too big for the channel with a small variation or too big for the channel with a small variation or too small for the channel with a large variation. The method presented in this paper has a simple structure and shows a new model employing the combination of the fixed step size method and variable step size method which results in compensatingthe disadvantages mentioned above. This paper also evaluates the performance inthe fundamental channel model.

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A Study On The Economic Value Of Firm's Big Data Technologies Introduction Using Real Option Approach - Based On YUYU Pharmaceuticals Case - (실물옵션 기법을 이용한 기업의 빅데이터 기술 도입의 경제적 가치 분석 - 유유제약 사례를 중심으로 -)

  • Jang, Hyuk Soo;Lee, Bong Gyou
    • Journal of Internet Computing and Services
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    • v.15 no.6
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    • pp.15-26
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    • 2014
  • This study focus on a economic value of the Big Data technologies by real options model using big data technology company's stock price to determine the price of the economic value of incremental assessed value. For estimating stochastic process of company's stock price by big data technology to extract the incremental shares, Generalized Moments Method (GMM) are used. Option value for Black-Scholes partial differential equation was derived, in which finite difference numerical methods to obtain the Big Data technology was introduced to estimate the economic value. As a result, a option value of big data technology investment is 38.5 billion under assumption which investment cost is 50 million won and time value is a about 1 million, respectively. Thus, introduction of big data technology to create a substantial effect on corporate profits, is valuable and there are an effects on the additional time value. Sensitivity analysis of lower underlying asset value appear decreased options value and the lower investment cost showed increased options value. A volatility are not sensitive on the option value due to the big data technological characteristics which are low stock volatility and introduction periods.

Observations of Solar Filaments with Fast Imaging Solar Spectrograph of the 1.6 meter New Solar Telescope at Big Bear Solar Observatory

  • Song, Dong-Uk;Park, Hyung-Min;Chae, Jong-Chul;Yang, Hee-Su;Park, Young-Deuk;Nah, Ja-Kyoung;Cho, Kyung-Suk;Jang, Bi-Ho;Ahn, Kwang-Su;Cao, Wenda;Goode, Philip R.
    • The Bulletin of The Korean Astronomical Society
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    • v.36 no.2
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    • pp.88.2-88.2
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    • 2011
  • Fast Imaging Solar Spectrograph (FISS) is an instrument developed by Seoul National University and Korea Astronomy and Space Science Institute and installed at the 1.6 meter New Solar Telescope of Big Bear Solar Observatory. Using this instrument, we observed solar filaments and analyzed the data focusing on determining the temperature and non-thermal velocity. We inferred the Doppler absorption widths of $H{\alpha}$ and Ca II 8542$\bar{A}$ lines from the line profiles using the cloud model. From these values, we separately determined temperature and non-thermal velocity. Our first result came from a solar filament observed on 2010 July 29th. Temperature inside a small selected region of this ranges from 4500K to 12000K and non-thermal velocity, from 3.5km/s to 7km/s. We also found temperature varied a lot with time. For example temperature at a fixed point varied from 8000K to 18000K for 40 minutes, displaying an oscillating pattern with a period of about 8 minutes and amplitude of about 2000K. We will also present new results from filaments observed in 2011 summer.

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A Study on Word Cloud Techniques for Analysis of Unstructured Text Data (비정형 텍스트 테이터 분석을 위한 워드클라우드 기법에 관한 연구)

  • Lee, Won-Jo
    • The Journal of the Convergence on Culture Technology
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    • v.6 no.4
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    • pp.715-720
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    • 2020
  • In Big data analysis, text data is mostly unstructured and large-capacity, so analysis was difficult because analysis techniques were not established. Therefore, this study was conducted for the possibility of commercialization through verification of usefulness and problems when applying the big data word cloud technique, one of the text data analysis techniques. In this paper, the limitations and problems of this technique are derived through visualization analysis of the "President UN Speech" using the R program word cloud technique. In addition, by proposing an improved model to solve this problem, an efficient method for practical application of the word cloud technique is proposed.

The Impact of Audit Characteristics on Firm Performance: An Empirical Study from an Emerging Economy

  • Rahman, Md. Musfiqur;Meah, Mohammad Rajon;Chaudhory, Nasir Uddin
    • The Journal of Asian Finance, Economics and Business
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    • v.6 no.1
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    • pp.59-69
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    • 2019
  • The auditor, an important instrument of corporate governance, ensures the transparency and accountability of the firm to the stakeholders. The objective of this paper is to explore the impact of audit characteristics on firm performance. In this study, external audit quality (BIG4), frequencies of audit committee meetings, and audit committee size are used as the proxies of audit characteristics and firm performance is measured through ROA, profit margin and EPS. A total of 503 firm years are considered as sample size from the listed manufacturing firms of Dhaka Stock Exchange (DSE) during the period of 2013 to 2017 to find out the impact of audit characteristics on firm performance. In this study, multivariate regression analysis is conducted using the pooled OLS method. Moreover, time dummy and lag model of multivariate analysis are also analyzed as robust check. The multivariate regression results find that external audit quality (BIG4) and audit committee size are significantly positively associated with firm performance. This study also finds that there is a significant negative relationship between audit committee meeting and firm performance. This study recommends that the regulatory authority and audit committee should review the frequencies of audit committee meeting to make it more effective to ensure better firm performance.

A study on the enhancement and performance optimization of parallel data processing model for Big Data on Emissions of Air Pollutants Emitted from Vehicles (차량에서 배출되는 대기 오염 물질의 빅 데이터에 대한 병렬 데이터 처리 모델의 강화 및 성능 최적화에 관한 연구)

  • Kang, Seong-In;Cho, Sung-youn;Kim, Ji-Whan;Kim, Hyeon-Joung
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.20 no.6
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    • pp.1-6
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    • 2020
  • Road movement pollutant air environment big data is a link between real-time traffic data such as vehicle type, speed, and load using AVC, VDS, WIM, and DTG, which are always traffic volume survey equipment, and road shape (uphill, downhill, turning section) data using GIS. It consists of traffic flow data. Also, unlike general data, a lot of data per unit time is generated and has various formats. In particular, since about 7.4 million cases/hour or more of large-scale real-time data collected as detailed traffic flow information are collected, stored and processed, a system that can efficiently process data is required. Therefore, in this study, an open source-based data parallel processing performance optimization study is conducted for the visualization of big data in the air environment of road transport pollution.

An Efficient Mixed-Integer Programming Model for Berth Allocation in Bulk Port (벌크항만의 하역 최적화를 위한 정수계획모형)

  • Tae-Sun, Yu;Yushin, Lee;Hyeongon, Park;Do-Hee, Kim;Hye-Rim, Bae
    • Journal of Korea Society of Industrial Information Systems
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    • v.27 no.6
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    • pp.105-114
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    • 2022
  • We examine berth allocation problems in tidal bulk ports with an objective of minimizing the demurrage and dispatch associated berthing cost. In the proposed optimization model inventory (or stock) level constraints are considered so as to satisfy the service level requirements in bulk terminals. It is shown that the mathematical programming formulation of this research provides improved schedule resolution and solution accuracy. We also show that the conventional big-M method of standard resource allocation models can be exempted in tidal bulk ports, and thus the computational efficiency can be significantly improved.

Wind tunnel test for the 20% scaled down NREL wind turbine blade (NREL 풍력터빈 블레이드 20% 축소모델 풍동시험 결과)

  • Cho, Taehwan;Kim, Cheolwan;Kim, Yangwon;Rho, Joohyun
    • 한국신재생에너지학회:학술대회논문집
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    • 2011.11a
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    • pp.33.2-33.2
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    • 2011
  • The 'NREL Phase VI' model with a 10.06m diameter was tested in the NASA Ames tunnel to make a reference data of the computational models. The test was conducted at the one rotational speed, blade tip speed 38m/s and the Reynolds number of the sectional airfoils in that test was around 1E6. The 1/5 scale down model of the 'NREL Phase VI' model was used in this paper to study the power characteristics in low Reynolds number region, 0.1E6 ~ 0.4E6 which is achievable range for the conventional wind tunnel facilities. The torque generated by the blade was directly measured by using the torque sensor installed in the rotating axis for a given wind speed and rotational speed. The power characteristics below the stall condition, lambda > 4, was presented in this paper. The power coefficient is very low in the condition below the Re. 0.2E6 and rapidly increases as the Re. increases. And it still increases but the variation is not so big in the condition above the Re. 0.3E6. This results shows that to study the performance of the wind turbine blade by using the scaled down model, the Re. should be larger than the 0.3E6.

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Transaction Pattern Discrimination of Malicious Supply Chain using Tariff-Structured Big Data (관세 정형 빅데이터를 활용한 우범공급망 거래패턴 선별)

  • Kim, Seongchan;Song, Sa-Kwang;Cho, Minhee;Shin, Su-Hyun
    • The Journal of the Korea Contents Association
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    • v.21 no.2
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    • pp.121-129
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    • 2021
  • In this study, we try to minimize the tariff risk by constructing a hazardous cargo screening model by applying Association Rule Mining, one of the data mining techniques. For this, the risk level between supply chains is calculated using the Apriori Algorithm, which is an association analysis algorithm, using the big data of the import declaration form of the Korea Customs Service(KCS). We perform data preprocessing and association rule mining to generate a model to be used in screening the supply chain. In the preprocessing process, we extract the attributes required for rule generation from the import declaration data after the error removing process. Then, we generate the rules by using the extracted attributes as inputs to the Apriori algorithm. The generated association rule model is loaded in the KCS screening system. When the import declaration which should be checked is received, the screening system refers to the model and returns the confidence value based on the supply chain information on the import declaration data. The result will be used to determine whether to check the import case. The 5-fold cross-validation of 16.6% precision and 33.8% recall showed that import declaration data for 2 years and 6 months were divided into learning data and test data. This is a result that is about 3.4 times higher in precision and 1.5 times higher in recall than frequency-based methods. This confirms that the proposed method is an effective way to reduce tariff risks.

A Study on the Design of Inquiry Instruction Model by Information Literacy Instruction in School Library (학교도서관의 정보활용교육에 의한 탐구수업모형 설계에 관한 연구)

  • Ro, Jin-Young;Byun, Woo-Yeoul;Lee, Byeong-Ki
    • Journal of Korean Library and Information Science Society
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    • v.40 no.1
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    • pp.471-492
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    • 2009
  • Inquiry instruction is a dynamic process that uses questioning and answering to have students actively participate in their own learning. Inquiry instruction is a teaching technique in which teachers do not provide knowledge, but help students discover knowledge by themselves. However, Inquiry instruction currently has problems of lack of connection between inquiry process and school library, lack of collaboration between the media specialist and teacher, and lack of applicable models. Information literacy is the ability to access, evaluate and use information. Information literacy process is closely related to the inquiry process. Thus, this study suggested an elaborative model in inquiry instruction using information literacy process. This research derived the skills, strategies, activities of inquiry instruction model by comparing and analyzing Lippitt's inquiry process with information literacy process(Big6 Skills, Pathways to Knowledge, I-Search, 8Ws, Inquiry Process, Inquiry in the Research Process). Based on the results, this study designed an elaborative model in inquiry instruction using information literacy process.

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