Adaptive bandwidth allocation algorithm based on the multi-threshold reservation mechanism by Geng CHEN, Wei-wei XIA, Lian-feng SHEN

“…An adaptive bandwidth allocation algorithm based on multi-threshold reservation mechanism is proposed to guarantee the quality of service (QoS) of multi-services in heterogeneous wireless networks.With the bandwidth reserva-tion mechanism by setting multi-threshold in each network for every traffic,the adaptive bandwidth allocation scheme according to the transmission rate levels requirements for traffic k and the network status can be formulated as an optimal problem with the constraints of the bandwidth allocation matrix for each traffic and all users based on the multi-homing technology.A procedure of the iterative method is presented to solve the optimal problem of the formulated adaptive bandwidth allocation scheme.The optimized bandwidth allocation matrixes for traffics and for all users are obtained for the real-time network throughput maximization under bandwidth reserving thresholds and network capacity constrains and the bandwidth resource utilization efficiency of heterogeneous wireless network can be increased.Numerical simula-tion results show that the proposed algorithm can support QoS requiring transmission rate grades,decrease the new call blocking probability,increase the average user access rate and improve the network throughput of the heterogeneous wireless network by 40% to the largest extent.…”
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A Comparative Study on Sensitivity-Based Damage Detection Methods in Bridges by Akbar Mirzaee, Reza Abbasnia, Mohsenali Shayanfar

“…Calculation of this massive matrix is repeated in each iteration and has a significant effect on the efficiency of method. …”
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Using Machine Learning Algorithm to Describe the Connection between the Types and Characteristics of Music Signal by Bo Sun

“…By comparing the experimental results, it is found that the classification accuracy of the deep confidence network model is higher than that of the logistic regression model, but the number of iterations needed for its accuracy to converge is also higher than that of the logistic regression model. …”
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Fast copy-move forgery detection algorithm based on group SIFT by Bin XIAO, Ruxia JING, Xiuli BI, Jianfeng MA

“…Aiming at the high computational complexity of the existing copy-move image forgery detection algorithm,a copy-move forgery detection algorithm based on group scale-invariant feature transform (SIFT) was proposed.Firstly,the simple linear iterative clustering (SLIC) was utilized to divide the input image into non-overlapping and irregular blocks.Secondly,the structure tensor was introduced to classify each block as flat blocks,edge blocks and corner blocks,and then the SIFT feature points extracted from the block were taken as the block features.Finally,the forgery was located by the inter-class matching of the block features.By means of inter-class matching and feature point matching,the time complexity of the proposed copy-move forgery detection algorithm in feature matching and locating forgery region was effectively reduced while guaranteeing the detection effect.The experimental results show that the accuracy of the proposed algorithm is 97.79%,the recall rate is 90.34%,and the F score is 93.59%,the detecting time for the image with size of 1024×768 is 12.72 s,and the detecting time for the image with size of 3000×2000 was 639.93 s.Compared with the existing copy-move algorithm,the proposed algorithm can locate the forgery region quickly and accurately,and has high robustness.…”
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Development of the Korean Version of the Drooling Infants and Preschoolers Scale by Kyoung Chul Min, Mi Young Hong, Ickpyo Hong, Hee Soon Woo

“…This study is aimed at translating and cross-culturally adapting the Drooling Infants and Preschoolers Scale (DRIPS) into Korean cultural context and examine the content validity and reliability of the Korean version, which is referred as K-DRIPS. Methods. An iterative forward-backward translation sequence of the DRIPS was performed by 20 Korean health professional experts (i.e., occupational therapists (OTs) and professors) with more than 10 years of experience. …”
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A Strongly A-Stable Time Integration Method for Solving the Nonlinear Reaction-Diffusion Equation by Wenyuan Liao

“…Rosenbrock method is efficient since it is iteration-free; however it suffers from order reduction when it is used for nonlinear parabolic partial differential equation. …”
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Enhancing AI-Inspired Analog Circuit Design: Optimizing Component Sizes with the Firefly Algorithm and Binary Firefly Algorithm by Trang Hoang

“…The Python-Spectre framework in this paper facilitates automatic, iterative simulation and data collection, driving the optimization process. …”
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Hyperparameter Optimization in Generative Adversarial Networks (GANs) Using Gaussian AHP by Thiago Serafim Rodrigues, Placido Rogerio Pinheiro

“…It applies Gaussian AHP to optimize hyperparameters based on multiple performance criteria, such as the quality of generated images, training stability, and training time. Iterative experiments validate the methodology by automatically adjusting hyperparameters based on the obtained scores, thereby maximizing the model’s efficiency and quality. …”
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Extending FABRIK with Obstacle Avoidance for Solving the Inverse Kinematics Problem by Songqiao Tao, Huajin Tao, Yumeng Yang

“…Since forward and backward teaching inverse kinematics (FABRIK) is a forward and backward iterative method that finds updated joint positions by locating a point on a line instead of using angle rotations or matrices, it has the advantages of fast convergence, low computational cost, and visualizing realistic poses. …”
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Adaptive Semiactive Cable Vibration Control: A Frequency Domain Perspective by Z. H. Chen, Y. Q. Ni

“…The Hilbert-Huang transform (HHT) technique is further synthesized for online tuning of the controller gain adaptively to track the cable vibration evolution, which also obviates the iterative optimal gain selection for the trade-off between control performance and energy in the conventional time domain LQG (T-LQG) control. …”
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Communication-Efficient Modeling with Penalized Quantile Regression for Distributed Data by Aijun Hu, Chujin Li, Jing Wu

“…The advantage of the proximal ADMM algorithm is that it could make every parameter of iteration to have closed formula even in high-dimensional case, which greatly improves the speed of calculation. …”
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Irreversible k-Threshold Conversion Number of Circulant Graphs by Ramy Shaheen, Suhail Mahfud, Ali Kassem

“…The irreversible k-threshold conversion process on a graph G=V,E is an iterative process which begins by choosing a set S0⊆V, and for each step tt=1,2,⋯,,St is obtained from St−1 by adjoining all vertices that have at least k neighbors in St−1. …”
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Understanding the lived experiences of Chinese lung cancer survivors: a qualitative analysis of blog entries by Xin Zhang, Yijin Wu

“…Each sentence in the eligible blog entries was determined as a unit of analysis and divided into meaning units, which were then coded and analyzed iteratively to generate subthemes and themes. The content analysis yielded five themes: (1) reasons for reluctance to accept their diagnosis; (2) treatment and its side effects; (3) emotional responses to their illness; (4) emotional support; (5) lung cancer disease management. …”
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Optimization of Daylighting, Ventilation, and Cooling Load Performance of Apartment in Tropical Ocean Area Based on Parametric Design by Jianjian Zhang, Lin Ji

“…The octopus plug-in in grasshopper is used to calculate the target value iteratively, so as to find the relative optimal value of multiobjective. …”
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Non-inertial opposition-based particle swarm optimization with adaptive elite mutation by Lan-lan KANG, Wen-yong DONG, Wan-juan SONG, Kang-shun LI

“…Non-inertia1 opposition-based partic1e swarm optimization with adaptive e1ite mutation（NOPSO）was proposed to overcome the drawbacks，such as，s1ow convergence speed，fa11ing into 1oca1 optimization，of opposition-based partic1e swarm optimization.In addition to increasing the diversity of popu1ation，two mechanisms were introduced to ba1ance the contradiction between exp1oration and exp1oitation during its iterations process.The first one was non-inertia1 ve1ocity（NIV）equation，which aimed to acce1erate the process of convergence of the a1gorithm via better access to and use of environmenta1 information.The second one was adaptive e1ite mutation strategy（AEM），which aimed to avoid trap into 1oca1 optimum.Experimenta1 resu1ts show NOPSO a1gorithm has stronger competitive abi1ity compared with opposition-based partic1e swarm optimizations and its varieties in both ca1cu1ation accuracy and computation cost.…”
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Solving Integral Equations by Means of Fixed Point Theory by E. Karapinar, A. Fulga, N. Shahzad, A. F. Roldán López de Hierro

“…One of the recent methodologies that is having great success in this field of study is the fixed point theory. Its iterative procedures are applicable to a great variety of contexts in which other algorithms fail. …”
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A National Synthetic Populations Dataset for the United States by James Rineer, Nicholas Kruskamp, Caroline Kery, Kasey Jones, Rainer Hilscher, Georgiy Bobashev

“…Census American Community Survey (ACS) 5-year estimates from the 2015–2019 ACS. We use Iterative Proportional Fitting (IPF) to create our synthetic population and use the resulting joint counts to sample representative households and people directly from microdata. …”
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Retina Modeling by Artificial Neural Networks by Amelia Stewart

“…The experimental findings demonstrate that including the output from earlier iterations as input to the neural network results in the system exhibiting memory. …”
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A multi-band spectrum sensing method based on sticky hidden Markov model by Zhongjie JIA, Ming JIN, Xiaoqun SONG

“…Existing multi-band spectrum sensing methods often use the sparsity of broadband spectrum.However, high spectrum occupancy rate of primary users degrades their performance severely.To address this issue, a novel multi-band spectrum sensing method was proposed by exploiting the state correlation among adjacent frequency bands.Firstly, a sticky hidden Markov model (SHMM) was established by regarding the multi-band states and measured energies as hidden and observed variables.In the SHMM, a sticky factor was introduced to represent the state correlation among adjacent frequency bands.Secondly, iterative expressions for the parameters of SHMM were derived.Finally, multi-band spectrum sensing was implemented by obtaining the posterior mean of observations from every frequency bands.Simulation results show that the proposed method outperforms existing methods, and when the false alarm probability is 0.1, the average frequency band occupancy rate is 50%, and the average signal-to-noise ratio is -12 dB, the detection probability can reach close to 0.99, which is about 30% higher than the detection probability of other methods.In addition, the proposed method had a faster convergence rate than existing methods and therefore has lower computational complexity.…”
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Research on the Influence of Composite Modification Design on Tooth Surface Wear of Transmission Gears by Bai Xiaoning, Li Yonghua, Wang Denglong, Zhang Dongxu

“…Finally, the optimal modification parameters are obtained through the iterative solution, and the composite modification design is carried out. …”
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