• Title/Summary/Keyword: polynomial regression analysis

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Engagement classification algorithm based on ECG(electrocardiogram) response in competition and cooperation games (심전도 반응 기반 경쟁, 협동 게임 참여자의 몰입 판단 알고리즘 개발)

  • Lee, Jung-Nyun;Whang, Min-Cheol;Park, Sang-In;Hwang, Sung-Teac
    • Journal of Korea Game Society
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    • v.17 no.2
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    • pp.17-26
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    • 2017
  • Excessive use of the internet and smart phones have become a social issue. The level of engagement has both positive and negative effects such as good performance or indulgence phenomenon, respectively. This study was to develop an algorithm to determine the engagement state based on cardiovascular response. The participants were asked to play a pattern matching game and the experimental design was divided into cooperation and competition task to provide the level of engagement. The correlation between heart rate and amplitude was analyzed according to each task. The regression equation and accuracy were verified by polynomial regression analysis. The results showed that heart rate and amplitude were positively correlated when the task was a game, and negatively correlated when there was a reference task. The accuracy of classifying between game and reference task was 89%. The accuracy between tasks was confirmed to be 76.5%. This study is expected to be used to quantitatively evaluate the level of engagement in real time.

Moving Object Tracking Scheme based on Polynomial Regression Prediction in Sparse Sensor Networks (저밀도 센서 네트워크 환경에서 다항 회귀 예측 기반 이동 객체 추적 기법)

  • Hwang, Dong-Gyo;Park, Hyuk;Park, Jun-Ho;Seong, Dong-Ook;Yoo, Jae-Soo
    • The Journal of the Korea Contents Association
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    • v.12 no.3
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    • pp.44-54
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    • 2012
  • In wireless sensor networks, a moving object tracking scheme is one of core technologies for real applications such as environment monitering and enemy moving tracking in military areas. However, no works have been carried out on processing the failure of object tracking in sparse sensor networks with holes. Therefore, the energy consumption in the existing schemes significantly increases due to plenty of failures of moving object tracking. To overcome this problem, we propose a novel moving object tracking scheme based on polynomial regression prediction in sparse sensor networks. The proposed scheme activates the minimum sensor nodes by predicting the trajectory of an object based on polynomial regression analysis. Moreover, in the case of the failure of moving object tracking, it just activates only the boundary nodes of a hole for failure recovery. By doing so, the proposed scheme reduces the energy consumption and ensures the high accuracy for object tracking in the sensor network with holes. To show the superiority of our proposed scheme, we compare it with the existing scheme. Our experimental results show that our proposed scheme reduces about 47% energy consumption for object tracking over the existing scheme and achieves about 91% accuracy of object tracking even in sensor networks with holes.

A study on motion errors due to acceleration and deceleration types of servo motors (서보모터의 가감속형태에 따른 운도오차에 관한 연구)

  • Shin, Dong-Soo;Chung, Sung-Chong
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.21 no.10
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    • pp.1718-1729
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    • 1997
  • This paper describes motion errors due to acceleration and deceleration types of servo motors in NC machine tools. Motion errors are composed of two components : one is due to transient response of a servomechanism and the other comes from gain mismatching of positioning servo motors. It deals with circular interpolation to identify motion errors by using Interface card. Also in order to minimize motion errors, this study presents an effective method to optimize parameters which are connected with motion errors. The proposed method is based upon a second order polynomial regression model and it includes an orthogonal array method to make the effective results of experiments. The validity and reliability of the study were verified on a vertical machining center equipped with FANUC 0MC through a series of experiments and analysis.

A Study on the Analysis of the Relationship between Sea Surface Temperature and Monthly Rainfall (해수면온도와 우리나라 월강우량과의 관계분석에 관한 연구)

  • Oh, Tae-Suk;Moon, Young-Il
    • Journal of Korea Water Resources Association
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    • v.43 no.5
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    • pp.471-482
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    • 2010
  • Rainfall events in the hydrologic circulation are closely related with various meteorological factors. Therefore, in this research, correlation relationship was analyzed between sea surface temperature of typical meteorological factor and monthly rainfall on Korean peninsula. The cluster analysis was performed monthly average rainfall data, longitude and latitude observed by rainfall observatory in Korea. Results from cluster analysis using monthly rainfall data in South Korea were divided into 4 regions. The principal components of monthly rainfall data were extracted from rainfall stations separated cluster regions. A correlation analysis was performed with extracted principal components and sea surface temperatures. At the results of correlation analysis, positive correlation coefficients were larger than negative correlation coefficients. In addition, The 3 month of principal components on monthly rainfall predicted by locally weighted polynomial regression using observed data of sea surface temperature where biggest correlation coefficients have. The result of forecasting through the locally weighted polynomial regression was revealed differences in accuracy. But, this methods in the research can be analyzed for forecasting about monthly rainfall data. Therefore, continuous research need through hydrological meteorological factors like a sea surface temperature about forecasting of the rainfall events.

Evaluation of Interlayer Shear Properties and Bonding Strengths of a Stress-Absorbing Membrane Interlayer and Development of a Predictive Model for Fracture Energy (덧씌우기 응력흡수층에 대한 전단, 부착강도 평가 및 파괴에너지 예측모델 개발)

  • Kim, Dowan;Mun, Sungho;Kwon, Ohsun;Moon, Kihoon
    • International Journal of Highway Engineering
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    • v.20 no.1
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    • pp.87-95
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    • 2018
  • PURPOSES : A geo-grid pavement, e.g., a stress-absorbing membrane interlayer (SAMI), can be applied to an asphalt-overlay method on the existing surface-pavement layer for pavement maintenance related to reflection cracking. Reflection cracking can occur when a crack in the existing surface layer influences the overlay pavement. It can reduce the pavement life cycle and adversely affect traffic safety. Moreover, a failed overlay can reduce the economic value. In this regard, the objective of this study is to evaluate the bonding properties between the rigid pavement and a SAMI by using the direct shear test and the pull-off test. The predicted fractural energy functions with the shear stress were determined from a numerical analysis of the moving average method and the polynomial regression method. METHODS : In this research, the shear and pull-off tests were performed to evaluate the properties of mixtures constructed using no interlayer, a tack-coat, and SAMI with fabric and without fabric. The lower mixture parts (describing the existing pavement) were mixed using the 25-40-8 joint cement-concrete standard. The overlay layer was constructed especially using polymer-modified stone mastic asphalt (SMA) pavement. It was composed of an SMA aggregate gradation and applied as the modified agent. The sixth polynomial regression equation and the general moving average method were utilized to estimate the interlayer shear strength. These numerical analysis methods were also used to determine the predictive models for estimating the fracture energy. RESULTS : From the direct shear test and the pull-off test results, the mixture bonded using the tack-coat (applied as the interlayer between the overlay layer and the jointed cement concrete) had the strongest shear resistance and bonding strength. In contrast, the SAMI pavement without fiber has a strong need for fractural energy at failure. CONCLUSIONS : The effects of site-reflection cracking can be determined using the same tests on cored specimens. Further, an empirical-mechanical finite-element method (FEM) must be done to understand the appropriate SAMI application. In this regard, the FEM application analy pavement-design analysis using thesis and bonding property tests using cored specimens from public roads will be conducted in further research.

Optimization of Gas Mixing-circulation Plasma Process using Design of Experiments (실험계획법을 이용한 가스 혼합-순환식 플라즈마 공정의 최적화)

  • Kim, Dong-Seog;Park, Young-Seek
    • Journal of Environmental Science International
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    • v.23 no.3
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    • pp.359-368
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    • 2014
  • The aim of our research was to apply experimental design methodology in the optimization of N, N-Dimethyl-4-nitrosoaniline (RNO, which is indictor of OH radical formation) degradation using gas mixing-circulation plasma process. The reaction was mathematically described as a function of four independent variables [voltage ($X_1$), gas flow rate ($X_2$), liquid flow rate ($X_3$) and time ($X_4$)] being modeled by the use of the central composite design (CCD). RNO removal efficiency was evaluated using a second-order polynomial multiple regression model. Analysis of variance (ANOVA) showed a high coefficient of determination ($R^2$) value of 0.9111, thus ensuring a satisfactory adjustment of the second-order polynomial multiple regression model with the experimental data. The application of response surface methodology (RSM) yielded the following regression equation, which is an empirical relationship between the RNO removal efficiency and independent variables in a coded unit: RNO removal efficiency (%) = $77.71+10.04X_1+10.72X_2+1.78X_3+17.66X_4+5.91X_1X_2+3.64X_2X_3-8.72X_2X_4-7.80X{_1}^2-6.49X{_2}^2-5.67X{_4}^2$. Maximum RNO removal efficiency was predicted and experimentally validated. The optimum voltage, air flow rate, liquid flow rate and time were obtained for the highest desirability at 117.99 V, 4.88 L/min, 6.27 L/min and 24.65 min, respectively. Under optimal value of process parameters, high removal(> 97 %) was obtained for RNO.

An improved polynomial model for top -and seat- angle connection

  • Prabha, P.;Marimuthu, V.;Jayachandran, S. Arul;Seetharaman, S.;Raman, N.
    • Steel and Composite Structures
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    • v.8 no.5
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    • pp.403-421
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    • 2008
  • The design provisions for semi-rigid steel frames have been incorporated in codes of practice for steel structures. In order to do the same, it is necessary to know the experimental moment-relative rotation (M-${\theta}_r$) behaviour of beam-to-column connections. In spite of numerous publications and collection of several connection databases, there is no unified approach for the semi-rigid design of steel frames. Amongst the many connection models available, the Frye-Morris polynomial model, with its limitations reported in the literature, is simple to adopt at least for the linear design space. However this model requires more number of connection tests and regression analyses to make it a realistic prediction model. In this paper, 3D nonlinear finite element (FE) analysis of beam-column connection specimens, carried out using ABAQUS software, for evaluating the M-${\theta}_r$ behaviour of semi-rigid top and seat-angle (TSA) bolted connections are described. The finite element model is validated against experimental behaviour of the same connection with regard to their moment-rotation behaviour, stress distribution and mode of failure of the connections. The calibrated FE model is used to evaluate the performance of the Frye-Morris polynomial model. The results of the numerical parametric studies carried out using the validated FE model have been used in proposing modifications to the Frye-Morris model for TSA connection in terms of the powers of the size parameters.

A Study on Polynomial Neural Networks for Stabilized Deep Networks Structure (안정화된 딥 네트워크 구조를 위한 다항식 신경회로망의 연구)

  • Jeon, Pil-Han;Kim, Eun-Hu;Oh, Sung-Kwun
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.66 no.12
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    • pp.1772-1781
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    • 2017
  • In this study, the design methodology for alleviating the overfitting problem of Polynomial Neural Networks(PNN) is realized with the aid of two kinds techniques such as L2 regularization and Sum of Squared Coefficients (SSC). The PNN is widely used as a kind of mathematical modeling methods such as the identification of linear system by input/output data and the regression analysis modeling method for prediction problem. PNN is an algorithm that obtains preferred network structure by generating consecutive layers as well as nodes by using a multivariate polynomial subexpression. It has much fewer nodes and more flexible adaptability than existing neural network algorithms. However, such algorithms lead to overfitting problems due to noise sensitivity as well as excessive trainning while generation of successive network layers. To alleviate such overfitting problem and also effectively design its ensuing deep network structure, two techniques are introduced. That is we use the two techniques of both SSC(Sum of Squared Coefficients) and $L_2$ regularization for consecutive generation of each layer's nodes as well as each layer in order to construct the deep PNN structure. The technique of $L_2$ regularization is used for the minimum coefficient estimation by adding penalty term to cost function. $L_2$ regularization is a kind of representative methods of reducing the influence of noise by flattening the solution space and also lessening coefficient size. The technique for the SSC is implemented for the minimization of Sum of Squared Coefficients of polynomial instead of using the square of errors. In the sequel, the overfitting problem of the deep PNN structure is stabilized by the proposed method. This study leads to the possibility of deep network structure design as well as big data processing and also the superiority of the network performance through experiments is shown.

Growth curve modeling of nucleus F0 on Korean accentual phrase

  • Yoon, Tae-Jin
    • Phonetics and Speech Sciences
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    • v.9 no.3
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    • pp.17-23
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    • 2017
  • The present study investigates the effect of Accentual Phrase on F0 using a subset of large-scale corpus of Seoul Korean. Four syllable words which were neither preceded nor followed by silent pauses were presumed to be canonical exemplars of Accentual Phrases in Korean. These four syllable words were extracted from female speakers' speech samples. Growth curve analyses, combination of regression and polynomial curve fitting, were applied to the four syllable words. Four syllable words were divided into four groups depending on the categorical status of the initial segment: voiceless obstruents, voiced obstruents, sonorants, and vowels. Results of growth curve analyses indicate that initial segment types have an effect on the F0 (in semitone) in the nucleus of the initial syllable, and the cubic polynomial term revealed that some of the medial low tones in the 4 syllable words may be guided by the principle of contrast maximization, while others may be governed by the principle of ease of articulation.

Evaluation of Extreme Rainfall based on Typhoon using Nonparametric Monte Carlo Simulation and Locally Weighted Polynomial Regression (비매개변수적 모의발생기법과 지역가중다항식을 이용한 태풍의 극치강우량 평가)

  • Oh, Tae-Suk;Moon, Young-Il;Chun, Si-Young;Kwon, Hyun-Han
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.29 no.2B
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    • pp.193-205
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    • 2009
  • Typhoons occurred in the tropical Pacific region, these might be affected the Korea moving toward north. The strong winds and the heavy rains by the typhoons caused a natural disaster in Korea. In the research, the heavy rainfall events based on typhoons were evaluated quantitative through various statistical techniques. First, probability precipitation and typhoon probability precipitation were compared using frequency analysis. Second, EST probability precipitation was calculated by Empirical Simulation Techniques (EST). Third, NL probability precipitation was estimated by coupled Nonparametric monte carlo simulation and Locally weighted polynomial regression. At the analysis results, the typhoons can be effected Gangneung and Mokpo stations more than other stations. Conversely, the typhoons can be effected Seoul and Inchen stations less than other stations. Also, EST and NL probability precipitation were estimated by the long-term simulation using observed data. Consequently, major hydrologic structures and regions where received the big typhoons impact should be review necessary. Also, EST and NL techniques can be used for climate change by the global warming. Because, these techniques used the relationship between the heavy rainfall events and the typhoons characteristics.