• Title/Summary/Keyword: Input indicator

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Qualitative Indicator Development of National Award for Innovation Leading Company (국가상 혁신기업선정을 위한 정성지표의 개발)

  • Lee, Jae-Ha
    • Journal of Convergence for Information Technology
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    • v.10 no.3
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    • pp.48-57
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    • 2020
  • This study focuses on the development of simple qualitative indicators for evaluating and selecting innovation leading companies that challenge National Award. Another purpose of this study is to complement the aspect in which the innovative or value of the companies' products, technologies, and services is only quantitatively evaluated. Existing evaluation indicators of national award have too many evaluation items and were not suitable for innovation-based company evaluation. The research approach is to select category for developing qualitative indicators based on previous studies and TF discussion. From the input-process-output-outcome point of view, we have set up an indicator system as a series of flows. Finally, five categories such as creativity, system excellence, customer value, performance, and ripple effects are selected as qualitative indicator. For these selected indicators, conceptual definitions and the main points of evaluation are described. And the system level evaluation and the ADLI approach are presented for reference. The appendix also includes examples of qualitative and quantitative evaluation of real companies using these indicators. However, this study implies the possibility that the evaluation results may vary depending on the level and perspective of the evaluator. We hoped that detailed research on candidate indicators that can be used as qualitative indicators and research on the development of mixed indicators(qualitative and quantitative) will continue in the future.

Forecasting Short-Term KOSPI using Wavelet Transforms and Fuzzy Neural Network (웨이블릿 변환과 퍼지 신경망을 이용한 단기 KOSPI 예측)

  • Shin, Dong-Kun;Chung, Kyung-Yong
    • The Journal of the Korea Contents Association
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    • v.11 no.6
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    • pp.1-7
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    • 2011
  • The methodology of KOSPI forecast has been considered as one of the most difficult problem to develop accurately since short-term KOSPI is correlated with various factors including politics and economics. In this paper, we presents a methodology for forecasting short-term trends of stock price for five days using the feature selection method based on a neural network with weighted fuzzy membership functions (NEWFM). The distributed non-overlap area measurement method selects the minimized number of input features by removing the worst input features one by one. A technical indicator are selected for preprocessing KOSPI data in the first step. In the second step, thirty-nine numbers of input features are produced by wavelet transforms. Twelve numbers of input features are selected as the minimized numbers of input features from thirty-nine numbers of input features using the non-overlap area distribution measurement method. The proposed method shows that sensitivity, specificity, and accuracy rates are 72.79%, 74.76%, and 73.84%, respectively.

A Study on The Dynamical Property of Input/output of Motion System for Machinery Control (기계 제어를 위한 모션시스템 입출력에 대한 동적 특성 연구)

  • Hyun, Sunghoon;Kim, Dongyon;Park, Janghwan
    • Journal of the Institute of Electronics and Information Engineers
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    • v.52 no.12
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    • pp.118-123
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    • 2015
  • The study of input and output characteristics in dynamic motion control is important indicator of the performance of mechanical equipment and is the factors to be considered during commissioning and maintenance of machinery or equipment, and project planning. The Analysis on dynamical characteristic of the input/output of the automation solution that used for motion control in machinery, is represented the control performance of device and including controller which connected at automation network by considering period of the frequency as applied load. This paper was constructed the simulator of B & R Powerlink to be widely used for motion control in the machine and showed the dynamic system characteristics by analysing the period.

An Accurate Stock Price Forecasting with Ensemble Learning Based on Sentiment of News (뉴스 감성 앙상블 학습을 통한 주가 예측기의 성능 향상)

  • Kim, Ha-Eun;Park, Young-Wook;Yoo, Si-eun;Jeong, Seong-Woo;Yoo, Joonhyuk
    • IEMEK Journal of Embedded Systems and Applications
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    • v.17 no.1
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    • pp.51-58
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    • 2022
  • Various studies have been conducted from the past to the present because stock price forecasts provide stability in the national economy and huge profits to investors. Recently, there have been many studies that suggest stock price prediction models using various input data such as macroeconomic indicators and emotional analysis. However, since each study was conducted individually, it is difficult to objectively compare each method, and studies on their impact on stock price prediction are still insufficient. In this paper, the effect of input data currently mainly used on the stock price is evaluated through the predicted value of the deep learning model and the error rate of the actual stock price. In addition, unlike most papers in emotional analysis, emotional analysis using the news body was conducted, and a method of supplementing the results of each emotional analysis is proposed through three emotional analysis models. Through experiments predicting Microsoft's revised closing price, the results of emotional analysis were found to be the most important factor in stock price prediction. Especially, when all of input data is used, error rate of ensembled sentiment analysis model is reduced by 58% compared to the baseline.

Lamb Production Costs: Analyses of Composition and Elasticities Analysis of Lamb Production Costs

  • Raineri, C.;Stivari, T.S.S.;Gameiro, A.H.
    • Asian-Australasian Journal of Animal Sciences
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    • v.28 no.8
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    • pp.1209-1215
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    • 2015
  • Since lamb is a commodity, producers cannot control the price of the product they sell. Therefore, managing production costs is a necessity. We explored the study of elasticities as a tool for basing decision-making in sheep production, and aimed at investigating the composition and elasticities of lamb production costs, and their influence on the performance of the activity. A representative sheep production farm, designed in a panel meeting, was the base for calculation of lamb production cost. We then performed studies of: i) costs composition, and ii) cost elasticities for prices of inputs and for zootechnical indicators. Variable costs represented 64.15% of total cost, while 21.66% were represented by operational fixed costs, and 14.19% by the income of the factors. As for elasticities to input prices, the opportunity cost of land was the item to which production cost was more sensitive: a 1% increase in its price would cause a 0.2666% increase in lamb cost. Meanwhile, the impact of increasing any technical indicator was significantly higher than the impact of rising input prices. A 1% increase in weight at slaughter, for example, would reduce total cost in 0.91%. The greatest obstacle to economic viability of sheep production under the observed conditions is low technical efficiency. Increased production costs are more related to deficient zootechnical indexes than to high expenses.

Adaptive K-best Sphere Decoding Algorithm Using the Characteristics of Path Metric (Path Metric의 특성을 이용한 적응형 K-best Sphere Decoding 기법)

  • Kim, Bong-Seok;Choi, Kwon-Hue
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.11A
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    • pp.862-869
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    • 2009
  • We propose a new adaptive K-best Sphere Decoding (SD) algorithm for Multiple Input Multiple Output (MIMO) systems where the number of survivor paths, K is changed based on the characteristics of path metrics which contain the instantaneous channel condition. In order to overcome a major drawback of Maximum Likelihood Detection (MLD) which exponentially increases the computational complexity with the number of transmit antennas, the conventional adaptive K-best SD algorithms which achieve near to MLD performance have been proposed. However, they still have redundant computation complexity since they only employ the channel fading gain as a channel condition indicator without instantaneous Signal to Noise Ratio (SNR) information. hi order to complement this drawback, the proposed algorithm use the characteristics of path metrics as a simple channel indicator. It is found that the ratio of the minimum path metric to the other path metrics reflects SNR information as well as channel fading gain. By adaptively changing K based on this ratio, the proposed algorithm more effectively reduce the computation complexity compared to the conventional K-best algorithms which achieve same performance.

A Study on Improvement of Means of Realization of Train Destination Equipment System (열차행선안내게시시스템 개선방안 연구)

  • Yoon, In-Young;Yeo, Yong-Joo;Kim, Kwang-Hwi;Kim, Ho-Chang
    • Proceedings of the KSR Conference
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    • 2007.11a
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    • pp.1566-1573
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    • 2007
  • Urban railway system that leads the urban public transportation enables the passengers to use the subway system safely and conveniently by indicating the destination of, status of approach of and other information on train through Train Destination Equipment(TDE), which is one of the important passenger services. The existing system is composed of Host Station Equipment(HSE) and operator panel that receives necessary input on train information from Total Traffic Control System(TTC), Local Station Equipment(LSE) that controls Train Destination Indicator(TDI) installed at each station, and Train Destination Indicator that ultimately displays train information to the passengers using the train system. This study aims to realize stabilized and reliable announcement system for destination of train by considering processing procedure and method of expression of inputted information of the existing system of notification of announcement of destination of train that can be applied in the RFID, which is the base technology of USN for which service expansion is easy, and to realize system that considers interface with USN and expandability with other facilities in the future.

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Usage of RSSI in WAVE Handover (WAVE 핸드오버상에서 수신 신호 세기의 이용)

  • Cho, Woong
    • The Journal of the Korea institute of electronic communication sciences
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    • v.7 no.6
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    • pp.1449-1454
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    • 2012
  • Received signal strength indicator (RSSI) represents the strength of the received signal at the front end of analog-to-digital convertor (ADC) input. RSSI value can be used for deciding the status of channel at the receiver. In this paper, the usage of RSSI in handover is studied using the practical measurement data. We first measure RSSI in 5.9GHz frequency band which is commonly used in wireless access in vehicular environments (WAVE) system. i.e., vehicular communications. Then, to implement a fast handover, the usability of RSSI data is analyzed based on the measured data. We also apply handover in practical highway environments.

Development of Program Evaluation Indicator : Community Health Center's Health Promotion Program (보건소 건강증진사업 평가지표 개발)

  • 송현종;진기남
    • Health Policy and Management
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    • v.13 no.4
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    • pp.1-27
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    • 2003
  • The purpose of this study was to develop the evaluation indicator for the health promotion programs of the Community Health Centers and to test its validity. The modified logic model was used as the evaluation model based on the literature reviews. Using this model, four dimensions, eleven sub­dimensions, and forty­one individual indicators were developed. These evaluation indicators are superior in reflecting the distinctiveness of the community health promotion programs, and also flexible enough to accommodate diverse programs. These indicators also emphasize the role of process evaluation, and the diversity of outcomes. To test content validity, survey method of experts in the community health promotion field was conducted. Eleven in three expert groups(professionals, practitioners in Community Health Centers, and policy makers) generally agreed with the validity of evaluation indicators. To examine criteria and construct validity, these indicators were used to evaluate the health promotion programs conducted by the 18 Key Community Health Centers. The data came from the interview surveys of the main health promotion practitioner and 30 visitors from each center. The ranks of these eighteen Community Health Centers were computed from these data. There was no significant difference in ranking either by these indicators or by the existing indicators, which was developed by Technical Support and Evaluation Team for criteria validity. There was no statistically significant difference in ranking between input, process and outcome dimensions. Based on these study results, evaluation indicators developed in this study are valid to evaluate Community Health Center's health promotion program. It can be used both by the Community Health Center for internal evaluation, and by the stakeholders for external evaluation.

Indoor Zone Recognition System using RSSI of BLE Beacon (BLE Beacons의 RSSI를 이용한 실내 Zone인식 시스템)

  • Kim, Jinpyung;Ahn, Taeki;Kim, Sanghoon;Ahn, Chi-Hyung
    • Journal of the Korean Society for Railway
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    • v.19 no.5
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    • pp.585-591
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    • 2016
  • Recently, indoor location detection has become an important area in the IoT (Internet of Things) environment for various indoor location-based services. In this paper, our proposed method shows that a virtual region can be divided electromagnetically according to specific facilities or services in various IoT application areas called zones. The MLP (Multi-Layer Perceptron) method is applied to recognize the service zone at the current position. The MLP utilized an RSSI (Received Signal Strength Indicator) signal of the BLE (Bluetooth Low Energy) Beacon as input data and made decisions to affiliate the zone of the current region as output. In order to verify the proposed method, we constructed an experimental environment similar in size to an actual rail station using four of the beacon and two zones.