A Fusion Approach of RSSI and LQI for Indoor Localization System Using Adaptive Smoothers by Sharly Joana Halder, Wooju Kim

“…The experimental results showed that the proposed mathematical method can reduce the average error around 25%, and it is always better than the other existing interference avoidance algorithms.…”
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Numerical Analysis of Unsaturated Soil Slopes under Rainfall Infiltration Based on the Modified Glasgow Coupled Model by Guoqing Cai, Mengzi Li, Bowen Han, Kenan Di, Qianqian Liu, Jian Li

“…Combined with Euler’s backward implicit integration algorithm, a numerical program was established for simulating the proposed model. …”
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SD‐SHO: Security‐dominated finite state machine state assignment technique with a satisfactory level of hardware optimization by Nitish Das, Aruna Priya Panchanathan

“…It is a deterministic algorithm and consists of two key techniques, such as state assignment using an improved quadratic sum code, and state assignment using a gradient‐based interior point method. …”
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An Elliptic Curve Based Schnorr Cloud Security Model in Distributed Environment by Vinothkumar Muthurajan, Balaji Narayanasamy

“…This paper proposes a virtual machine based cloud model with Hybrid Cloud Security Algorithm (HCSA) to remove the expired content. The HCSA-based auditing improves the malicious activity prediction during the data transfer. …”
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Iterative Signal Processing for Mitigation of Analog-to-Digital Converter Clipping Distortion in Multiband OFDMA Receivers by Markus Allén, Toni Levanen, Jaakko Marttila, Mikko Valkama

“…It is shown that the clipping compensation algorithm implemented in a turbo decoding OFDM receiver is able to remove almost all the clipping distortion even under significant clipping in fading channel circumstances. …”
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Preserving information while respecting privacy through an information theoretic framework for synthetic health data generation by Nadir Sella, Florent Guinot, Nikita Lagrange, Laurent-Philippe Albou, Jonathan Desponds, Hervé Isambert

“…Here, we introduce a novel algorithm (MIIC-SDG) for generating synthetic data from electronic records based on a multivariate information framework and Bayesian network theory. …”
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Accuracy-Improved Fault Diagnosis Method for Rolling Bearing Based on Enhanced ESGMD-CC and BA-ELM Model by Wei Yuan, Fuzheng Liu, Hongbin Gu, Fei Miao, Faye Zhang, Mingshun Jiang

“…In order to increase the accuracy of fault diagnosis, it proposes a new fault diagnosis method based on enhanced Symplectic geometry mode decomposition with cosine difference factor and calculus operator (ESGMD-CC) and bat algorithm (BA) optimized extreme learning machine (ELM). …”
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A comparison of nonlinear filtering approaches in the context of anHIV model by H. Thomas Banks, Shuhua Hu, Zackary R. Kenz, Hien T. Tran

“…Numerical experiments reveal thatthe GHF is the most computationally expensive algorithm, while theEKF is the least expensive one. …”
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Professional self-determination theory of senior pupils in Russian psychology by E. P. Shutova, A. S. Velikanova (Gerasimova)

“…Some researchers focus on the goal and end result of vocational self-determination, while others seek to reveal the algorithm of the process itself and/or its stages. …”
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Prediction of the Styrene Butadiene Rubber Performance by Emulsion Polymerization Using Backpropagation Neural Network by Yan-jiang Jin, Ben-xian Shen, Ruo-fan Ren, Lei Yang, Jun Sui, Ji-gang Zhao

“…The backpropagation neural network was trained by the original formula and ameliorated formula on the basis of Levenberg-Marquardt algorithm, and the relative error between the simulation results and experimental data is less than 1%. …”
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A CLUSTERING TECHNIQUE FOR THE VIETNAMESE WORD CATEGORIZATION by Nguyễn Minh Hiệp, Nguyễn Thị Minh Huyền, Ngô Thế Quyền, Trần Thị Phương Linh

“…This paper presents an application of the DBSCAN clustering algorithm to classify Vietnamese words from a large corpus. …”
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Fault Diagnosis Method for Bearing of High-Speed Train Based on Multitask Deep Learning by Jia Gu, Ming Huang

“…Firstly, the operating condition parameters of the high-speed train are analyzed and identified, and the K-means algorithm is used to classify and identify the operating condition of the high-speed train. …”
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Improved Power Control Using Optimal Adjustable Coefficients for Three-Phase Photovoltaic Inverter under Unbalanced Grid Voltage by Qianggang Wang, Niancheng Zhou, Xiaoxuan Lou, Xu Chen

“…Through the optimization algorithm, the coefficients can be determined aiming to generate the minimum integrated amplitudes of the active and reactive power references with the constraints of the inverter current and DC voltage fluctuation. …”
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Optimum Synthesis of Pencil Beams with Constrained Dynamic Range Ratio by Marko Matijascic, Maja Jurisic Bellotti, Mladen Vucic, Goran Molnar

“…By incorporating these problems into a branch and bound algorithm, the procedures for global optimizations are formed which systematically search the space of all coefficient signs. …”
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Comparative Glycopeptide Analysis for Protein Glycosylation by Liquid Chromatography and Tandem Mass Spectrometry: Variation in Glycosylation Patterns of Site-Directed Mutagenized... by Young Hye Hahm, Sung Ho Hahm, Hyoun Young Jo, Yeong Hee Ahn

“…In this study, glycopeptide mapping of a reference and biosimilar recombinant antibodies (rAbs) was performed using liquid chromatography-electrospray ionization tandem mass spectrometry (LC-ESI-MS/MS) and an automated Glycoproteome Analyzer (GPA) algorithm. The tandem mass analyses for the reference and biosimilar samples indicate that this approach proves to be highly efficient in reproducing consistent analytical results and discovering the implications of different rAb production methods on glycosylation patterns. …”
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Design and implementation of state-of-charge estimation based on back-propagation neural network for smart uninterruptible power system by Shuo Li, Song Li, Haifeng Zhao, Yuan An

“…Then, the back-propagation neural network is trained by Levenberg–Marquardt algorithm and gradient descent method; and the state of charge of batteries in uninterruptible power system is estimated by the trained back-propagation neural network. …”
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Fixed start method for repetitive project scheduling with simulated annealing by Francisco Moreno, Eric Forcael, Francisco Orozco, Felipe Baesler, Duzgun Agdas

“…To achieve this, a Fixed Start Method (FSM) —where the starts of each activity with a high level of probabilistic confidence for the planned project duration are fixed— was applied, where the high level of probabilistic confidence obtained was optimized with the use of the metaheuristic algorithm called Simulated Annealing (SA). This procedure evaluated the project completion in a case study based on the coefficient of variance (COV) of the resulting standard deviation, mean, and temperature selected for the SA. …”
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The Use of Machine Learning Approaches for the Diagnosis of Acute Appendicitis by Omer F. Akmese, Gul Dogan, Hakan Kor, Hasan Erbay, Emre Demir

“…It was found that the gradient boosted trees algorithm achieves the best success with an accurate prediction success of 95.31%. …”
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Reliability Assessment of Steel-Concrete Composite Beams considering Metal Corrosion Effects by Trong-Ha Nguyen, Duy-Duan Nguyen

“…The developed reliability analysis algorithm in this study is verified with previous studies, highlighting the capability of the used method. …”
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Optimization and Modeling of Optical Emission Spatial Coverage from Underwater Multi-Faceted Optical Base Stations by Junjie Shi, Chunbo Ma, Xu Tian, Hanjun Guo, Jun Ao

“…Additionally, a Multi-Objective Particle Swarm Optimization (MOPSO) algorithm is used to optimize the configuration of the multi-faceted LED array by adjusting the deflection angles of the LED arrays and the emission half-angle of the LEDs at the OBS. …”
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