Journal articles: 'Online smoothing'

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Chen, Sixia, and Alexander Russell. "Online Metric Tracking and Smoothing." Algorithmica 68, no. 1 (June 28, 2012): 133–51. http://dx.doi.org/10.1007/s00453-012-9669-8.

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Mann, B. L. "Smoothing Some Wrinkles in Online Dispute Resolution." International Journal of Law and Information Technology 17, no. 1 (November 21, 2008): 83–112. http://dx.doi.org/10.1093/ijlit/ean017.

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Cao, Guohong, Wu-chi Feng, and Mukesh Singhal. "Online variable-bit-rate video traffic smoothing." Computer Communications 26, no. 7 (May 2003): 639–51. http://dx.doi.org/10.1016/s0140-3664(02)00197-4.

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Jiang, Wei, and Yongzhong Zhu. "Online process mean estimation usingL1norm exponential smoothing." Naval Research Logistics 56, no. 5 (August 2009): 439–49. http://dx.doi.org/10.1002/nav.20351.

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Cai, Qingzhong, Gongliu Yang, Ningfang Song, Jianye Pan, and Yiliang Liu. "An Online Smoothing Method Based on Reverse Navigation for ZUPT-Aided INSs." Journal of Navigation 70, no. 2 (October 21, 2016): 342–58. http://dx.doi.org/10.1017/s0373463316000667.

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Zero velocity update (ZUPT) is widely discussed for error restriction in land vehicle Inertial Navigation Systems (INSs) and wearable pedestrian INSs to overcome the problems of Global Positioning System (GPS) unavailability in urban canyons or indoor scenarios. In this paper, an online smoothing method for ZUPT-aided INSs is presented. By introducing the Rauch–Tung–Striebel (RTS) smoothing method into the ZUPT-aided INS, position errors can be effectively restrained not only at stop points but during the whole trajectory. By integrating reverse navigation with a ZUPT smoother, the method realises forward and real-time processing. Compared with existing approaches, it can improve the position accuracy in real time without any other sensors, which is well suited for applications on high-accuracy navigation in GPS-challenging environments. Accuracy test results with different Inertial Measurement Units (IMUs) show that the developed method can significantly decrease position errors from hundreds or thousands of metres to below ten metres. During the whole trajectory, the online smoothing method ensures the maximum position errors at non-stop points can reach the same level of accuracy at stop points. A delay test result proves that the delay of the reverse online smoothing method proposed in this paper is much shorter than existing online smoothing methods.

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Duffield, Samuel, and Sumeetpal Singh. "Online Particle Smoothing With Application to Map-Matching." IEEE Transactions on Signal Processing 70 (2022): 497–508. http://dx.doi.org/10.1109/tsp.2022.3141259.

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Sen, S., J. L. Rexford, J. K. Dey, J. F. Kurose, and D. F. Towsley. "Online smoothing of variable-bit-rate streaming video." IEEE Transactions on Multimedia 2, no. 1 (March 2000): 37–48. http://dx.doi.org/10.1109/6046.825793.

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Einbeck, Jochen, and Göran Kauermann. "Online monitoring with local smoothing methods and adaptive ridging." Journal of Statistical Computation and Simulation 73, no. 12 (December 2003): 913–29. http://dx.doi.org/10.1080/0094965031000104332.

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Ekadjaja, Agustin, Andre Chuandra, and Margarita Ekadjaja. "THE IMPACT OF BOARD INDEPENDENCE, PROFITABILITY, LEVERAGE, AND FIRM SIZE ON INCOME SMOOTHING IN CONTROL OF AGENCY CONFLICT." Jurnal Ekonomi Manajemen Sistem Informasi 1, no. 3 (February 27, 2020): 238–47. http://dx.doi.org/10.31933/jemsi.v1i3.104.

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This research is aimed to earn empirical results about the effect of board independence, profitability, leverage and firm size on income smoothing. The study used purposive sampling as its sampling method on manufacture companies that’s listed on BEI for years 2015-2017. Information for this research was acquired from multiple online sources that store financial reports of companies. This research used Eckel Index to determine if a corporation did an income smoothing on its financial report or not. The results were significant relationships between board independence and income smoothing and between profitability and income smoothing while insignificant relationships were found in between leverage and income smoothing and between firm size and income smoothing. To improve this study there are mulitple ways that has been written in conclusion part.

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Ekadjaja, Agustin, Andre Chuandra, and Margarita Ekadjaja. "THE IMPACT OF BOARD INDEPENDENCE, PROFITABILITY, LEVERAGE, AND FIRM SIZE ON INCOME SMOOTHING IN CONTROL OF AGENCY CONFLICT." Dinasti International Journal of Education Management And Social Science 1, no. 3 (February 19, 2020): 388–99. http://dx.doi.org/10.31933/dijemss.v1i3.169.

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This research is aimed to earn empirical results about the effect of board independence, profitability, leverage and firm size on income smoothing. The study used purposive sampling as its sampling method on manufacture companies that’s listed on BEI for years 2015-2017. Information for this research was acquired from multiple online sources that store financial reports of companies. This research used Eckel Index to determine if a corporation did an income smoothing on its financial report or not. The results were significant relationships between board independence and income smoothing and between profitability and income smoothing while insignificant relationships were found in between leverage and income smoothing and between firm size and income smoothing. To improve this study there are mulitple ways that has been written in conclusion part.

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Samanta, O., U. Bhattacharya, and S. K. Parui. "Smoothing of HMM parameters for efficient recognition of online handwriting." Pattern Recognition 47, no. 11 (November 2014): 3614–29. http://dx.doi.org/10.1016/j.patcog.2014.04.019.

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Lakhdar, Yissam, and El Hassan Sbai. "Online Variable Kernel Estimator." International Journal of Operations Research and Information Systems 8, no. 1 (January 2017): 58–92. http://dx.doi.org/10.4018/ijoris.2017010104.

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In this work, the authors propose a novel method called online variable kernel estimation of the probability density function (pdf). This new online estimator combines the characteristics and properties of two estimators namely nearest neighbors estimator and the Parzen-Rosenblatt estimator. Their approach allows a compact online adaptation of the estimated probability density function from the new arrival data. The performance of the online variable kernel estimator (OVKE) depends on the choice of the bandwidth. The authors present in this article a new technique for determining the optimal smoothing parameter of OVKE based on the maximum entropy principle (MEP). The robustness and performance of the proposed approach are demonstrated by examples of online estimation of real and simulated data distributions.

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Sologub, G. B., V. A. Pukhov, and L. S. Tsyplenkov. "Tsyplenkov L.S. Predicting the Number of Teachers Needed at Online-School." Моделирование и анализ данных 10, no. 2 (2020): 39–48. http://dx.doi.org/10.17759/mda.2020100203.

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The article describes an approach to forecasting the number of teachers to hire by an online English language school, based on an analysis of historical data on the lessons using linear regression and triple exponential smoothing models.

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Xu, Yan, Zhi Qiang Wang, and Qing Yang. "Real-Time Variance Calculation Method for Synchronous System Clock Based on Adaptive Exponential Smoothing." Applied Mechanics and Materials 513-517 (February 2014): 1555–60. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.1555.

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An adaptive clock variance calculation algorithm is designed to improve the real-time characteristics and complexity of general method. This algorithm use the latency and smoothing characteristics of exponential smoothing to achieve real-time calculation online. Using this algorithm, synchronous system can response to environmental changes in a short time. The test result shows that the real-time characteristics and output robustness can be improved obviously.

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Xu, Yuan, and Xiyuan Chen. "Online cubature Kalman filter Rauch–Tung–Striebel smoothing for indoor inertial navigation system/ultrawideband integrated pedestrian navigation." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 232, no. 4 (May 31, 2017): 390–98. http://dx.doi.org/10.1177/0959651817711627.

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Accurate position information of the pedestrians is required in many applications such as healthcare, entertainment industries, and military field. In this work, an online Cubature Kalman filter Rauch–Tung–Striebel smoothing algorithm for people’s location in indoor environment is proposed using inertial navigation system techniques with ultrawideband technology. In this algorithm, Cubature Kalman filter is employed to improve the filtering output accuracy; then, the Rauch–Tung–Striebel smoothing is used between the ultrawideband measurements updates; finally, the average value of the corrected inertial navigation system error estimation is output to compensate the inertial navigation system position error. Moreover, a real indoor test has been done for assessing the performance of the proposed model and algorithm. Test results show that the proposed model is able to reduce the sum of the absolute position error between the east direction and the north direction by about 32% compared with only the ultrawideband model, and the performance of the online Cubature Kalman filter Rauch–Tung–Striebel smoothing algorithm is slightly better than the off-line mode.

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Lin, Faa-Jeng, Su-Ying Lu, Jo-Yu Chao, and Jin-Kuan Chang. "Intelligent PV Power Smoothing Control Using Probabilistic Fuzzy Neural Network with Asymmetric Membership Function." International Journal of Photoenergy 2017 (2017): 1–15. http://dx.doi.org/10.1155/2017/8387909.

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An intelligent PV power smoothing control using probabilistic fuzzy neural network with asymmetric membership function (PFNN-AMF) is proposed in this study. First, a photovoltaic (PV) power plant with a battery energy storage system (BESS) is introduced. The BESS consisted of a bidirectional DC/AC 3-phase inverter and LiFePO4 batteries. Then, the difference of the actual PV power and smoothed power is supplied by the BESS. Moreover, the network structure of the PFNN-AMF and its online learning algorithms are described in detail. Furthermore, the three-phase output currents of the PV power plant are converted to the dq-axis current components. The resulted q-axis current is the input of the PFNN-AMF power smoothing control, and the output is a smoothing PV power curve to achieve the effect of PV power smoothing. Comparing to the other smoothing methods, a minimum energy capacity of the BESS with a small fluctuation of the grid power can be achieved by the PV power smoothing control using PFNN-AMF. In addition, a personal computer- (PC-) based PV power plant emulator and BESS are built for the experimentation. From the experimental results of various irradiance variation conditions, the effectiveness of the proposed intelligent PV power smoothing control can be verified.

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Satriawan, Cil Hardianto, and Dessi Puji Lestari. "Average Window Smoothing for an Indonesian Language Online Speaker Identification System." International Journal on Electrical Engineering and Informatics 10, no. 4 (December 30, 2018): 726–37. http://dx.doi.org/10.15676/ijeei.2018.10.4.7.

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Chang, Ray-I., Meng-Chang Chen, Jan-Ming Ho, and Ming-Tat Ko. "Online traffic smoothing for delivery of variable bit rate media streams." Circuits, Systems, and Signal Processing 20, no. 3-4 (May 2001): 341–59. http://dx.doi.org/10.1007/bf01201406.

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Zimmermann, Roger, Cyrus Shahabi, Kun Fu, and Mehrdad Jahangiri. "A multi-threshold online smoothing technique for variable rate multimedia streams." Multimedia Tools and Applications 28, no. 1 (January 2006): 23–49. http://dx.doi.org/10.1007/s11042-006-5119-4.

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Khamaludin, Khamaludin. "PERAMALAN PENJUALAN HIJAB SXPROJECT MENGGUNAKAN METODE MOVING AVERAGE DAN EXPONENTIAL SMOOTHING." UNISTEK 6, no. 2 (August 31, 2019): 13–16. http://dx.doi.org/10.33592/unistek.v6i2.249.

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Penjualan hijab online di Indonesia sedang mengalami kenaikan yang cukup pesat. Penjual hijab online merajalela di situs-situs e-commerce salah satunya online shop sxproject ini. Selain peningkatan pada banyaknya penjual hijab, peningkatan juga terjadi pada konsumen pengguna hijab itu sendiri. Dengan tingginya peminat hijab, penjual atau produsen harus menyiasati produksi penjualan mereka agar dapat mencapai target dan tidak membuat stok terlalu banyak. Untuk mengetahui berapa yang harus diproduksi oleh penjual pada tahun berikutnya, penjual dapat melakukan perhitungan peramalan. Berdasarkan perhitungan dengan menggunakan metode rata-rata bergerak dan penghalusan eksponensial dengan tingkat kesalahan menggunakan MAD, MSE, dan MAPE. Berdasarkan perhitungan dengan dua metode tersebut dan tingkat kesalahan diperoleh metode terbaiknya adalah metode rata-rata bergerak 4 bulan.

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Lin, Faa-Jeng, Shih-Gang Chen, and Jin-Kuan Chang. "Intelligent Wind Power Smoothing Control using Fuzzy Neural Network." E3S Web of Conferences 69 (2018): 01006. http://dx.doi.org/10.1051/e3sconf/20186901006.

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An intelligent wind power smoothing control using fuzzy neural network (FNN) is proposed in this study. First, the modeling of wind power generator and the designed battery energy storage system (BESS) are introduced. The BESS is consisted of a bidirectional interleaved DC/DC converter and a 3-arm 3-level inverter. Then, the network structure of the FNN and its online learning algorithms are described in detail. Moreover, actual wind data is adopted as the input to the designed wind power generator model. Furthermore, the three-phase output currents of the wind power generator are converted to dq-axis current components. The resulted q-axis current is the input of the FNN power smoothing control and the output is a gentle wind power curve to achieve the effect of wind power smoothing. The difference of the actual wind power and smoothed power is supplied by the BESS. Comparing to the other smoothing methods, a minimum energy capacity of the BESS with a small fluctuation of the grid power can be achieved by the FNN power smoothing control. In the experimentation, a digital signal processor (DSP) based BESS is built using two TMS320F28335. From the experimental results of various wind variation sceneries, the effectiveness of the proposed intelligent wind power smoothing control is verified.

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Wu, Guangxin, ZongWu Xie, ChuangQiang Guo, and Hong Liu. "Kalman smoothing with soft inequality constraints for space robot teleoperation." International Journal of Advanced Robotic Systems 15, no. 1 (January 1, 2018): 172988141774602. http://dx.doi.org/10.1177/1729881417746024.

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Space robot teleoperation system with haptic device has two operation modes: offline teleoperation mode and online teleoperation mode. High acceleration and jerk produced by the teleoperation system may degrade the performance of trajectory tracking and cause large residual vibration. In this article, human hand is treated as a kind of sensor, and two smoothers based on the standard Kalman smoother have been proposed to limit the acceleration and jerk in joint space in a certain range. On the one hand, the offline smoother for offline teleoperation mode makes use of a smoothing algorithm proposed in the literature, which is based on the interior point techniques. On the other hand, the online smoother for online teleoperation mode is proposed and named as reduced-Q method, which is a fixed-lag smoother with adjustable measurement noise. Experimental results have shown that the methods can constrain the acceleration and jerk of the trajectories in joint space within the specified range approximately and can improve the tracking accuracy without causing too many deformations. Thus, the psychology burden of operator will be alleviated.

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Kim, Minseung, Sein Cheong, Hyungchan Song, and Jong Won Shin. "Improved Speech Spatial Covariance Matrix Estimation for Online Multi-Microphone Speech Enhancement." Sensors 23, no. 1 (December 22, 2022): 111. http://dx.doi.org/10.3390/s23010111.

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Online multi-microphone speech enhancement aims to extract target speech from multiple noisy inputs by exploiting the spatial information as well as the spectro-temporal characteristics with low latency. Acoustic parameters such as the acoustic transfer function and speech and noise spatial covariance matrices (SCMs) should be estimated in a causal manner to enable the online estimation of the clean speech spectra. In this paper, we propose an improved estimator for the speech SCM, which can be parameterized with the speech power spectral density (PSD) and relative transfer function (RTF). Specifically, we adopt the temporal cepstrum smoothing (TCS) scheme to estimate the speech PSD, which is conventionally estimated with temporal smoothing. Furthermore, we propose a novel RTF estimator based on a time difference of arrival (TDoA) estimate obtained by the cross-correlation method. Furthermore, we propose refining the initial estimate of speech SCM by utilizing the estimates for the clean speech spectrum and clean speech power spectrum. The proposed approach showed superior performance in terms of the perceptual evaluation of speech quality (PESQ) scores, extended short-time objective intelligibility (eSTOI), and scale-invariant signal-to-distortion ratio (SISDR) in our experiments on the CHiME-4 database.

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Albab, M. Ulul, Elly Anjarsari, Rahma Febriyanti, and Marissa Dewi Fatimah. "Prediksi Deret Waktu Manajemen Lalu Lintas." Jurnal Axioma : Jurnal Matematika dan Pembelajaran 8, no. 1 (April 13, 2023): 59–71. http://dx.doi.org/10.56013/axi.v8i1.1988.

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Optimizing customer service for the number of drivers in an area through real-time transportation service industry online to scale up. In this paper, the dataset used is traffic management accompanied by attributes such as level 6 geohash, day, timestamp, and demand. The dataset used is a sample from geohash6 coded qp0991, containing online transportation demands from 01/04/2018 until 31/05/2018 (61 days). The training datasets are from the qp0991 code sample, starting from 01/04/2018 until 10/05/2018 and the remaining datasets are used as the testing datasets. The percentages for training and testing are respectively 67% and 33%. The methods applied to construct the objective function are three different forecasting methods, namely the Naïve approach, auto-regressive integrated moving average (ARIMA), and simple exponential smoothing. The results of this study indicate that the simple exponential smoothing method is better than the naïve approach and auto-regressive integrated moving average based on the root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE). The simple exponential smoothing has an accuracy rate of 98.7% for the RMSE value, 98.9% for the MAE value, and 88.81% for the MAPE value. Keywords: time series, traffic management

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Alenlov, Johan, and Jimmy Olsson. "Particle-Based Adaptive-Lag Online Marginal Smoothing in General State-Space Models." IEEE Transactions on Signal Processing 67, no. 21 (November 1, 2019): 5571–82. http://dx.doi.org/10.1109/tsp.2019.2941066.

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Zhang, Huisheng, and Yanli Tang. "Online gradient method with smoothing ℓ 0 regularization for feedforward neural networks." Neurocomputing 224 (February 2017): 1–8. http://dx.doi.org/10.1016/j.neucom.2016.10.057.

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Olsson, Jimmy, and Johan Westerborn. "Efficient particle-based online smoothing in general hidden Markov models: The PaRIS algorithm." Bernoulli 23, no. 3 (August 2017): 1951–96. http://dx.doi.org/10.3150/16-bej801.

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Lin, J. W., R. I. Chang, J. M. Ho, and F. Lai. "FOS: A Funnel-Based Approach for Optimal Online Traffic Smoothing of Live Video." IEEE Transactions on Multimedia 8, no. 5 (October 2006): 996–1004. http://dx.doi.org/10.1109/tmm.2006.879868.

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Liu, Di, Daniel Percival, and Stephen Fienberg. "User Interest and Interaction Structure in Online Forums." Proceedings of the International AAAI Conference on Web and Social Media 4, no. 1 (May 16, 2010): 283–86. http://dx.doi.org/10.1609/icwsm.v4i1.14059.

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We present a new similarity measure tailored to posts in an online forum. Our measure takes into account all the available information about user interest and interaction — the content of posts, the threads in the forum, and the author of the posts. We use this post similarity to build a similarity between users, based on principal coordinate analysis. This allows easy visualization of the user activity as well. Similarity between users has numerous applications, such as clustering or classification. We show that including the author of a post in the post similarity has a smoothing effect on principal coordinate projections. We demonstrate our method on real data drawn from an internal corporate forum, and compare our results to those given by a standard document classification method. We conclude our method gives a more detailed picture of both the local and global network structure.

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Wagner, Philipp, Xinyang Wu, and Marco F. Huber. "Kalman Bayesian Neural Networks for Closed-Form Online Learning." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 8 (June 26, 2023): 10069–77. http://dx.doi.org/10.1609/aaai.v37i8.26200.

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Compared to point estimates calculated by standard neural networks, Bayesian neural networks (BNN) provide probability distributions over the output predictions and model parameters, i.e., the weights. Training the weight distribution of a BNN, however, is more involved due to the intractability of the underlying Bayesian inference problem and thus, requires efficient approximations. In this paper, we propose a novel approach for BNN learning via closed-form Bayesian inference. For this purpose, the calculation of the predictive distribution of the output and the update of the weight distribution are treated as Bayesian filtering and smoothing problems, where the weights are modeled as Gaussian random variables. This allows closed-form expressions for training the network's parameters in a sequential/online fashion without gradient descent. We demonstrate our method on several UCI datasets and compare it to the state of the art.

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Iskander, C. D., and P. T. Mathiopoulos. "Online Smoothing of VBR H.263 Video for the CDMA2000 and IS-95B Uplinks." IEEE Transactions on Multimedia 6, no. 4 (August 2004): 647–58. http://dx.doi.org/10.1109/tmm.2004.830808.

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Wylie, Dennis C., Hans A. Hofmann, and Boris V. Zemelman. "SArKS: de novo discovery of gene expression regulatory motif sites and domains by suffix array kernel smoothing." Bioinformatics 35, no. 20 (March 23, 2019): 3944–52. http://dx.doi.org/10.1093/bioinformatics/btz198.

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Abstract Motivation We set out to develop an algorithm that can mine differential gene expression data to identify candidate cell type-specific DNA regulatory sequences. Differential expression is usually quantified as a continuous score—fold-change, test-statistic, P-value—comparing biological classes. Unlike existing approaches, our de novo strategy, termed SArKS, applies non-parametric kernel smoothing to uncover promoter motif sites that correlate with elevated differential expression scores. SArKS detects motif k-mers by smoothing sequence scores over sequence similarity. A second round of smoothing over spatial proximity reveals multi-motif domains (MMDs). Discovered motif sites can then be merged or extended based on adjacency within MMDs. False positive rates are estimated and controlled by permutation testing. Results We applied SArKS to published gene expression data representing distinct neocortical neuron classes in Mus musculus and interneuron developmental states in Homo sapiens. When benchmarked against several existing algorithms using a cross-validation procedure, SArKS identified larger motif sets that formed the basis for regression models with higher correlative power. Availability and implementation https://github.com/denniscwylie/sarks. Supplementary information Supplementary data are available at Bioinformatics online.

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Yuanfei, Zhang. "A Personalized Recommendation System for English Teaching Resources Based on Learning Behavior Detection." Mobile Information Systems 2022 (September 7, 2022): 1–8. http://dx.doi.org/10.1155/2022/4531867.

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When confronted with a plethora of resources, many students struggle to quickly filter out the content that is relevant to them. Because there are many English teaching resources and it is difficult to accurately recommend suitable teaching resources for students. Therefore, in this paper we suggest a personalized recommendation system for English teaching resources, which is founded on learning behavior detection. To begin with, a spatiotemporal convolutional network is introduced to effectively identify students’ online classroom behavior, and a global attention module is added to increase the model’s ability to learn global feature information. Furthermore, the identified characteristics of student behavior are incorporated into the recommendation module. Similarly, the differential evolution (DE) algorithm is implemented to the smoothing factor and kernel function center of a generalized regression neural network (CRNN) for resource recommendation mode, while taking into account the strong dependence of the GRNN training effect on the smoothing factor and the kernel function center. The smoothing factor and offset factor are optimized and solved, and the optimized smoothing factor and offset factor are used to recommend GRNN resources. Experiments show that the approach described in this work first has a high precision (i.e., 90.98%) in behavior recognition, and second, the recommendation performance is superior to both of the comparison algorithms (i.e., 85.23% and 78.33%), resulting in better resource recommendation accuracy. The fundamental goal of this work is to deliver several important guidelines for the informatization and intelligence of the English educational resources and services.

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Mhammed, Naufel B., Soran Ab M. Saeed, and Avan M. Ahmed. "EOG signal Modeling using Double Exponential Smoothing for Robot Arm Control System." Kurdistan Journal of Applied Research 2, no. 3 (August 27, 2017): 260–66. http://dx.doi.org/10.24017/science.2017.3.47.

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This paper present a novel way of modeling EOG signal to use in a robot arm control system, two procedures implemented, offline procedure to measure and modeling EOG for building a pattern reference model ,and online procedure used to Control the robot arm. By comparing online measured EOG and the EOG pattern in reference model suitable manipulation instruction generated by the micro controller. The double exponential smoothing method used for building the pattern reference model, the accuracy of the reference model tested with main squire error (MSE) and main absolute error (MAPE) measures. Auto correlation analysis applied to study the existing pattern and linearity of EOG signal with eye movements. EOG signal measurement for this research classified in to five kinds: EOG horizontal (left and right) Vertical (up and down), and blinking. The EOG signal models of this research saved and used as a reference model file to classify the eye movements. a measurement and robot arm control system constructed by using arduino olimix 328, olimix sensor shield, and robot arm driving circuit, arduino C used as a programming environment, Minitab software used to build the model and correlation analysis ,Brain Bay software used to control and signal processing.

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Zhang, Yixing, Shunli Wang, and Wenhua Xu. "An improved smoothing factor-extended kalman filtering method for accurate online state-of-charge estimation of Lithium-ion battery." Journal of Physics: Conference Series 2232, no. 1 (May 1, 2022): 012011. http://dx.doi.org/10.1088/1742-6596/2232/1/012011.

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Abstract The state of charge of battery is an important index of battery management system. The Lithium-ion batteries are widely used in various industries, so they are full of uncertainty, which makes them difficult to estimate the state of charge of Lithium-ion batteries. To solve the problem of low accuracy and large variability in real-time estimation of Lithium-ion batteries, taking Lithium-ion batteries as the research object, the Thevenin model is used to simulate the working characteristics. On the basis of the extended Kalman filtering algorithm, through the influence of the covariance matrix and noise, a smoothing factor is introduced to increase the Kalman gain and improve flexibility. Experiments have proved that the smoothing factor-extended Kalman algorithm improves the flexibility of the algorithm, and at the same time reduces the non-linear error caused by the rapid charging and discharging changes of Lithium-ion batteries. In the Hybrid Pulse Power Characterization test, the maximum estimation error is 0.14%, and the average estimation error is 0.1%. It provides a new method for estimating the state of charge of Lithium-ion batteries.

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Abed, Mustafa S., Omar F. Lutfy, and Qusay F. Al-Doori. "Online Optimization Application on Path Planning in Unknown Environments." Journal Européen des Systèmes Automatisés 55, no. 1 (February 28, 2022): 61–69. http://dx.doi.org/10.18280/jesa.550106.

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For autonomous mobile robots, determining the shortest path to the target is an indispensable requirement. In this work, two modifications of the Grey Wolf Optimization (GWO) method, which are called MGWO1 and MGWO2, are suggested for online path planning to make the mobile robot reach the goal using the shortest path and safely avoiding the obstacles in unknown environments. To avoid sharp curves, a cost function is derived using a path smoothing parameter and an integrated distance function. The results of the proposed approach are presented based on computer simulation in various unknown environments. A study was conducted to compare the performance of the proposed algorithm with those of other algorithms and the results indicated that the proposed GWO, MGWO1, and MGWO2 algorithms are competent in avoiding obstacles successfully including the local minima situation. Finally, the average enhancement rate in path length compared with Adaptive Particle Swarm Optimization (APSO), GWO is 5.30%, MGWO1 is 5.52%, and MGWO2 is 7.44%.

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Lubis, Jopandi Syahputra, Irvan Irvan, and Dedy Irwan. "RANCANG BANGUNG SISTEM INFORMASI BOOKING TEMPAT PADA SALON LELY GUNA MEMUDAHKAN KONSUMEN BERBASIS WEB." Syntax : Journal of Software Engineering, Computer Science and Information Technology 4, no. 1 (June 20, 2023): 308–13. http://dx.doi.org/10.46576/syntax.v4i1.2891.

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Salon Lely merupakan salah satu toko kecantikan yang berlokasi di Jl.AR.Hakim, Gg. Rahayu II No.1 B Medan. Salon Lely ini menyediakan jasa perawatan rambut dan kecantikan seperti potong rambut, creambath, smoothing, rebonding, hair toning, hair colouring, catok, keriting, facial dan layanan salon lainnya. Permasalahan sering terjadi di salon lely sering terjadinya antrian panjang saat customer datang ke lokasi yang mengakibatkan harus mengantri terlebih dahulu, para customer juga tidak bisa melakukan pemesanan online tanpa datang langsung ke lokasi salon. Berangkat dari permasalahan diatas penulis coba membuat aplikasi sistem informasi pemesanan tempat guna meningkatkan pelayanan kepada customer tujuan dilakukannnya penelitian ini yaitu untuk menyediakan fasilitas pelayanan konsumen berupa pemesanan yang dapat dilakukan secara online dan dari penelitian menghasilkan Aplikasi sistem informasi pemesanan salon Lely dapat mempermudah pelanggan dalam melakukan pemesanan secara online Kata Kunci : Salon Lely, Sistem Informasi, Pemesanan Online, Konsumen

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Adams, Samuel Olorunfemi, and Godwin Somto. "Comparative Study of the Error Trend and Seasonal Exponential Smoothing and ARIMA Model using COVID-19 Death Rate in Nigeria." International Journal of Natural Sciences Research 10, no. 1 (June 23, 2022): 43–53. http://dx.doi.org/10.18488/63.v10i1.3031.

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In the last two years, COVID-19 had claimed millions of life in Nigeria and the world at large. It is an established global health emergency of our time and an ongoing threat faced by the world up till now. This study aims to determine the trend, fit an appropriate Error Trend and Seasonal (ETS) exponential smoothing and ARIMA model to the COVID-19 daily deaths in Nigeria. Dataset on the daily COVID-19 confirmed death cases were utilized in the study. The data was extracted from the Nigerian Centre for Disease Control (NCDC) online database from 10th July 2020 to 2nd December 2021. Autoregressive Integrated Moving Average (ARIMA) and twelve (12) (ETS) exponential smoothing techniques were compared based on the dataset. The performance of the ARIMA and ETS exponential smoothing methods was investigated using the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), Hannan Quinn Information Criterion (HQC), and AMSE selection criteria. The best time series modeling for the coronavirus (COVID-19) epidemic in Nigeria was the ARIMA (0,1,0) because its model selection criteria showed that it had the lowest value of; AIC=2863.51, BIC= 2866.90, HQ = 2866.90, and AMSE = 0.55471. ARIMA (0,1,0) model is preferred among the thirteen (13) competing models based on daily confirmed deaths due to COVID-19 in Nigeria.

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Chen, Xiyuan, Yuan Xu, and Qinghua Li. "Application of Adaptive Extended Kalman Smoothing on INS/WSN Integration System for Mobile Robot Indoors." Mathematical Problems in Engineering 2013 (2013): 1–8. http://dx.doi.org/10.1155/2013/130508.

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The inertial navigation systems (INS)/wireless sensor network (WSN) integration system for mobile robot is proposed for navigation information indoors accurately and continuously. The Kalman filter (KF) is widely used for real-time applications with the aim of gaining optimal data fusion. In order to improve the accuracy of the navigation information, this work proposed an adaptive extended Kalman smoothing (AEKS) which utilizes inertial measuring units (IMUs) and ultrasonic positioning system. In this mode, the adaptive extended Kalman filter (AEKF) is used to improve the accuracy of forward Kalman filtering (FKF) and backward Kalman filtering (BKF), and then the AEKS and the average filter are used between two output timings for the online smoothing. Several real indoor tests are done to assess the performance of the proposed method. The results show that the proposed method can reduce the error compared with the INS-only, least squares (LS) solution, and AEKF.

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Fan, Qinwei, Jacek M. Zurada, and Wei Wu. "Convergence of online gradient method for feedforward neural networks with smoothing L1/2 regularization penalty." Neurocomputing 131 (May 2014): 208–16. http://dx.doi.org/10.1016/j.neucom.2013.10.023.

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Doran, Derek, Swapna S. Gokhale, and Aldo Dagnino. "Discovering Perceptions in Online Social Media: A Probabilistic Approach." International Journal of Software Engineering and Knowledge Engineering 24, no. 09 (November 2014): 1273–99. http://dx.doi.org/10.1142/s0218194014400129.

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People across the world habitually turn to online social media to share their experiences, thoughts, ideas, and opinions as they go about their daily lives. These posts collectively contain a wealth of insights into how masses perceive their surroundings. Therefore, extracting people's perceptions from social media posts can provide valuable information about pertinent issues such as public transportation, emergency conditions, and even reactions to political actions or other activities. This paper proposes a novel approach to extract such perceptions from a corpus of social media posts originating from a given broad geographical region. The approach divides the broad region into a number of sub-regions, and trains language models over social media conversations within these sub-regions. Using Bayesian and geo-smoothing methods, the ensemble of language models can be queried with phrases embodying a perception. Discrete and continuous visualization methods represent the extent to which social media posts within the sub-regions express the query. The capabilities of the perception mining approach are illustrated using transportation-themed scenarios.

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Purnama Sari, Wahyu, Yiyi Supendi, and Badar Abdi Mulya. "SISTEM MONITORING ALOKASI DANA DESA DENGAN METODE EXPONENTIAL SMOOTHING." Naratif Jurnal Nasional Riset Aplikasi dan Teknik Informatika 3, no. 01 (June 28, 2021): 17–24. http://dx.doi.org/10.53580/naratif.v3i01.114.

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Sistem Monitoring Alokasi Dana Desa dengan Metode Exponential Smoothing merupakan sebuah sistem yang dikembangkan untuk memantau pengalokasian dana desa yang dilakukan di kelurahan agar dapat memudahkan pendataan dan keterbukaan bagi kepala desa dan masyarakat terkait pengalokasian dana desa. Sistem monitoring alokasi dana desa ini diharapkan menjadi solusi dalam upaya pendataan alokasi dana desa yang saat ini masih dilakukan secara manual. Dokumen-dokumen fisik/hardcopy yang digunakan, menyebabkan laporan yang dihasilkan tidak akurat, penyelesaian pembuatan laporan yang membutuhkan waktu lama, dan kemungkinan terjadinya kehilangan laporan yang disebabkan karena tidak terdokumentasinya laporan-laporan tersebut dengan baik. Faktor-faktor ini akan menyebabkan sulitnya monitoring terhadap dana desa yang disalurkan dari pemerintah. Adapun tujuan dari pengembangan sistem monitoring ini adalah untuk memudahkan masyarakat agar dapat mengetahui alokasi dana desa secara online menggunakan aplikasi, memudahkan administrasi dalam memberikan informasi terkait alokasi dana yang dikeluarkan kepada masyarakat, memudahkan pendataan dibidang administrasi keuangan kelurahan dan memudahkan merekap data alokasi dana desa untuk melakukan prediksi pengeluaran dibulan selanjutnya. Laporan yang diharapkan dari sistem monitoring ini adalah adanya transparansi dana desa yang diketahui dari laporan data dan grafik untuk dari penggunaan dana desa saat ini dan untuk mendapatkan evaluasi dana untuk tahun berikutnya, Metode penelitian yang digunakan dalam penelitian ini adalah metode deskriptif dengan model pengembangan perangkat lunak menggunakan Model Rapid Application Development (RAD).

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Dębski, Roman, and Rafał Dreżewski. "Adaptive Segmentation of Streaming Sensor Data on Edge Devices." Sensors 21, no. 20 (October 17, 2021): 6884. http://dx.doi.org/10.3390/s21206884.

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Sensor data streams often represent signals/trajectories which are twice differentiable (e.g., to give a continuous velocity and acceleration), and this property must be reflected in their segmentation. An adaptive streaming algorithm for this problem is presented. It is based on the greedy look-ahead strategy and is built on the concept of a cubic splinelet. A characteristic feature of the proposed algorithm is the real-time simultaneous segmentation, smoothing, and compression of data streams. The segmentation quality is measured in terms of the signal approximation accuracy and the corresponding compression ratio. The numerical results show the relatively high compression ratios (from 135 to 208, i.e., compressed stream sizes up to 208 times smaller) combined with the approximation errors comparable to those obtained from the state-of-the-art global reference algorithm. The proposed algorithm can be applied to various domains, including online compression and/or smoothing of data streams coming from sensors, real-time IoT analytics, and embedded time-series databases.

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Sabila, Tasya Kurnia, Lelah Lelah, and Didik Indrayana. "Sistem Prediksi Penjualan di Toko Dasni Menggunakan Metode Double Exponential Smoothing." Pixel :Jurnal Ilmiah Komputer Grafis 15, no. 2 (December 6, 2022): 305–12. http://dx.doi.org/10.51903/pixel.v15i2.813.

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Dalam mengembangkan suatu usaha atau penjualan adalah dengan mengikuti perkembangan teknologi termasuk penggunaan sistem untuk interaksi jual beli. Sudah banyak pedagang yang melakukan interaksi jual beli secara online. Selain itu, untuk mengembangkan suatu usaha juga diperlukan yang namanya prediksi penjualan pada masa yang akan datang agar penjual mengetahui dan mempersiapkan jumlah barang yang akan terjual untuk menghindari kekurangan ataupun kelebihan jumlah barang. Untuk mencari prediksi penjualan tersebut dapat dilakukan dengan berbagai metode salah satunya yaitu metode Double Exponential Smoothing. Metode Double Exponential Smoothing merupakan metode runtut waktu yang menggunakan data dari masa lampau untuk diprediksi pada periode selanjutnya. Data yang diolah yaitu data penjualan pada Toko Pakaian Dasni selama satu tahun. Hasil yang didapatkan berupa sistem prediksi penjualan selama 3 bulan periode selanjutnya yang dihitung tingkat keakuratan prediksi menggukan MAPE (Mean Absolute Percentage Error) dengan dicari error terkecil karena semakin kecil error maka semakin akurat untuk memprediksi jumlah penjualan pada periode selanjutnya. Sistem prediksi ini juga dirancang menggunakan bahasa pemrograman PHP.

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Klein, Joshua, Luis Carvalho, and Joseph Zaia. "Application of network smoothing to glycan LC-MS profiling." Bioinformatics 34, no. 20 (May 22, 2018): 3511–18. http://dx.doi.org/10.1093/bioinformatics/bty397.

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Abstract Motivation Glycosylation is one of the most heterogeneous and complex protein post-translational modifications. Liquid chromatography coupled mass spectrometry (LC-MS) is a common high throughput method for analyzing complex biological samples. Accurate study of glycans require high resolution mass spectrometry. Mass spectrometry data contains intricate sub-structures that encode mass and abundance, requiring several transformations before it can be used to identify biological molecules, requiring automated tools to analyze samples in a high throughput setting. Existing tools for interpreting the resulting data do not take into account related glycans when evaluating individual observations, limiting their sensitivity. Results We developed an algorithm for assigning glycan compositions from LC-MS data by exploring biosynthetic network relationships among glycans. Our algorithm optimizes a set of likelihood scoring functions based on glycan chemical properties but uses network Laplacian regularization and optionally prior information about expected glycan families to smooth the likelihood and thus achieve a consistent and more representative solution. Our method was able to identify as many, or more glycan compositions compared to previous approaches, and demonstrated greater sensitivity with regularization. Our network definition was tailored to N-glycans but the method may be applied to glycomics data from other glycan families like O-glycans or heparan sulfate where the relationships between compositions can be expressed as a graph. Availability and implementation Built Executable http://www.bumc.bu.edu/msr/glycresoft/ and Source Code: https://github.com/BostonUniversityCBMS/glycresoft. Supplementary information Supplementary data are available at Bioinformatics online.

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Chleboun, Jan, Thulio Amorim, Ana Maria Nascimento, and Tiago P. Nascimento. "An Improved Spanning Tree-Based Algorithm for Coverage of Large Areas Using Multi-UAV Systems." Drones 7, no. 1 (December 23, 2022): 9. http://dx.doi.org/10.3390/drones7010009.

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In this work, we propose an improved artificially weighted spanning tree coverage (IAWSTC) algorithm for distributed coverage path planning of multiple flying robots. The proposed approach is suitable for environment exploration in cluttered regions, where unexpected obstacles can appear. In addition, we present an online re-planner smoothing algorithm with unexpected detected obstacles. To validate our approach, we performed simulations and real robot experiments. The results showed that our proposed approach produces sub-regions with less redundancy than its previous version.

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Fahrudin, Tresna Maulana, Prismahardi Aji Riyantoko, Kartika Maulida Hindrayani, and I. Gede Susrama Mas Diyasa. "Daily Forecasting for Antam's Certified Gold Bullion Prices in 2018-2020 using Polynomial Regression and Double Exponential Smoothing." Journal of International Conference Proceedings 3, no. 4 (January 26, 2021): 45–53. http://dx.doi.org/10.32535/jicp.v3i4.1009.

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Gold investment is currently a trend in society, especially the millennial generation. Gold investment for the younger generation is an advantage for the future. Gold bullion is often used as a promising investment, on other hand, the digital gold is available which it is stored online on the gold trading platform. However, any investment certainly has risks, and the price of gold bullion fluctuates from day to day. People who invest in gold hopes to benefit from the initial purchase price even if they must wait up to five years. The problem is how they can notice the best time to sell and buy gold. Therefore, this research proposes a forecasting approach based on time series data and the selling of gold bullion prices per gram in Indonesia. The experiment reported that Holt’s double exponential smoothing provided better forecasting performance than polynomial regression. Holt’s double exponential smoothing reached the minimum of Mean Absolute Percentage Error (MAPE) 0.056% in the training set, 0.047% in one-step testing, and 0.898% in multi-step testing.

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Josyula, Siva Phaniram, and Reddy M. Babu. "Deep Convolutional Neural Network with a Stochastic Gradient Descent Optimizer (PDCNN-SGD) model for telugu character recognition." i-manager’s Journal on Image Processing 10, no. 1 (2023): 1. http://dx.doi.org/10.26634/jip.10.1.19250.

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Telugu Character Recognition (TCR) has received significant attention because of the drastic increase in technological advancements such as multimedia, smartphones and iPods, and paper documents. Offline character recognition is the process of identifying Telugu characters from the scanned image or document whereas online character recognition enables to recognition of characters by the machine while the user writes. Several researchers have attempted to design online TCR models by the use of distinct classification models and feature extraction approaches. It is still necessary to construct automated and intelligent online TCR models, even if many studies have focused on offline TCR models. The Telugu character dataset construction and validation using an Inception and ResNet-based model are presented. The collection of 645 letters in the dataset includes 18 Achus, 38 Hallus, 35 Othulu, 34*16 Guninthamulu and 10 Ankelu. The proposed technique aims to efficiently recognize and identify distinctive Telugu characters online. This model's main preprocessing steps to achieve its goals include normalization, smoothing, and interpolation. Improved recognition performance can be attained by using Stochastic Gradient Descent (SGD) to optimize the model's hyperparameters.

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Chen, Fan, Liu Tianbo, Hu Guihua, Yang Minglei, and Long Jian. "Online Determination on the Properties of Naphtha as the Ethylene Feedstock Using Near-Infrared Spectroscopy." Нефтехимия 63, no. 5 (December 15, 2023): 688–700. http://dx.doi.org/10.31857/s0028242123050076.

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Providing real-time information on the properties of naphtha as the ethylene feedstock within the minimal time is significant for improvement of the process simulation, control, and real-time optimization. To develop models predicting naphtha properties for different pre-processing methods, an online full transmittance near-infrared (NIR) spectrum measurement system has been used along with the principal component regression and partial least squares (PLS) methods. The results show that the Savitzky-Golay smoothing combined with the first-derivative pre-processing provides the best denoising effect compared to other methods. The predicted relative errors of the NIR models developed by PLS, especially for the cutting temperature points of the test set, basically make 1‒5% indicating it can be used to create good NIR prediction models for the on-line determination of naphtha properties.

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Miao, Qian, Feng Yan, and Ya Nan Liu. "Voltage Track Prediction Based on WAMS." Applied Mechanics and Materials 325-326 (June 2013): 652–55. http://dx.doi.org/10.4028/www.scientific.net/amm.325-326.652.

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In order to give online voltage monitoring and stability margin judgment, a radial basis function (RBF) is used in this paper to predict the node voltage amplitude. Using BPA build IEEE9 network and input the processed data to RBF neural network, compared the results with the actual voltage amplitude, got a accurate prediction result. So as to stand out the accuracy of RBF, compared the relative error of prediction results between RBF and the second exponential smoothing model (SES). It testified the accuracy of RBF was more superior.

Journal articles on the topic 'Online smoothing'

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