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Journal articles on the topic 'AR algorithm'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Lei, Yue. "Design of Digital Media Advertisement from the Perspective of Base Image Schema Based on Web." Mobile Information Systems 2022 (August 8, 2022): 1–8. http://dx.doi.org/10.1155/2022/2362760.

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With the development of improved augmented reality (AR) devices, the use of AR in new media to better communicate culture has become a major trend. However, AR technology algorithms still have many shortcomings, and this paper proposes a new algorithm that shows that the proposed algorithm is better than traditional terrain generation algorithms in terms of display and granularity and less costly than traditional geographic algorithms, according to the proposed algorithm, traditional genealogy algorithms and terrain sequencing algorithms. Therefore, the proposed area adjustment algorithm in th

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Liu, Xiao Yong. "Design of RBF Neural Networks Based on Adjustable Radius." Key Engineering Materials 439-440 (June 2010): 605–10. http://dx.doi.org/10.4028/www.scientific.net/kem.439-440.605.

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In this paper, a new RBF neural network (RBFNN) algorithm, called ar-RBFNN, is presented. In traditional RBFNNs based on clustering algorithm, called oRBFNN in this paper, the width of the basis function-Gaussian function, or called radius, ignored the effect of numbers in different clusters, or density of data points. New algorithm considers radius is effect to performance of algorithms in problem of function approximation. Mean Square Error is used to evaluate performances of two algorithms, oRBFNN and ar-RBFNN algorithms. Several experiments in function approximation show ar-RBFNN is better

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He, Shufang, Yang Qiu, and Jing Xu. "Invalid-Resource-Aware Spectrum Assignment for Advanced-Reservation Traffic in Elastic Optical Network." Sensors 20, no. 15 (2020): 4190. http://dx.doi.org/10.3390/s20154190.

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Elastic optical networks (EONs) can make service accommodation more flexible and precise by employing efficient routing and spectrum allocation (RSA) algorithms. In order to improve the efficiency of RSA algorithms, the advanced-reservation technique was introduced into designing RSA algorithms. However, few of these advanced-reservation-based RSA algorithms were focused on the unavailable spectrum resources in EONs. In this paper, we propose an Advanced-Reservation-based Invalid-Spectrum-Aware (AR-ISA) resource allocation algorithm to improve the networking performance and the resource alignm

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Ali, Muhammad Ali Rushdi, and Mohammad Alturki Alaa. "Computation of k-out-of-n System Reliability via Reduced Ordered Binary Decision Diagrams." British Journal of Mathematics & Computer Science 22, no. 3 (2017): 1–9. https://doi.org/10.9734/BJMCS/2017/33642.

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A prominent reliability model is that of the partially-redundant (k-out-of-n) system. We use algebraic as well as signal-flow-graph methods to explore and expose the AR algorithm for computing k-out-of-n reliability. We demonstrate that the AR algorithm is, in fact, both a recursive and an iterative implementation of the strategy of Reduced Ordered Binary Decision Diagrams (ROBDDs). The underlying ROBDD for the AR recursive algorithm is represented by a compact Signal Flow Graph (SFG) that is used to deduce AR iterative algorithms of quadratic temporal complexity and linear spatial complexity.

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Chen, Jun, Bo Li, and Er Fei Wang. "Parallel Scheduling Algorithms Investigation of Support Strict Resource Reservation from Grid." Applied Mechanics and Materials 519-520 (February 2014): 108–13. http://dx.doi.org/10.4028/www.scientific.net/amm.519-520.108.

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This paper studies resource reservation mechanisms in the strict parallel computing grid,and proposed to support the parallel strict resource reservation request scheduling model and algorithms, FCFS and EASY backfill analysis of two important parallel scheduling algorithm, given four parallel scheduling algorithms supporting resource reservation. Simulation results of four algorithms of resource utilization, job bounded slowdown factor and the success rate of Advanced Reservation (AR) jobs were studied. The results show that the EASY backfill + firstfit algorithm can ensure QoS of AR jobs whi

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Sharma, Sachin, Deepak Thakur, and DR A. J. Singh. "Study of Various Computer Vision Algorithms for Registration in Augmented Reality: A Survey." International Journal for Research in Applied Science and Engineering Technology 12, no. 7 (2024): 283–87. http://dx.doi.org/10.22214/ijraset.2024.63550.

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Abstract: Augmented reality is defined as the fusion of virtual object in real world. Registration is basic step for creating an immersive AR experience to the user. The registration algorithms helps in placing the virtually created object in the most accurate position in the real world. This paper shows an in-depth comparative analysis of various registration algorithm under computer vision that are used for AR applications. The comparative analysis helps in identifying the strengths, weaknesses and the applicability of each algorithm in various AR fields by studying different case studies an

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Zhao, Ya Hui, Hong Li Wang, and Rong Yi Cui. "Abnormal Voice Detection Algorithm Based on Semi-Supervised Co-Training Algorithm." Advanced Materials Research 461 (February 2012): 117–22. http://dx.doi.org/10.4028/www.scientific.net/amr.461.117.

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The AR-Tri-training algorithm is proposed for applying to the abnormal voice detection, and voice detection software is designed by mixed programming used Matlab and VC in this paper. Firstly, training samples are collected and the features of each sample are extracted including centroid, spectral entropy, wavelet and MFCC. Secondly, the assistant learning strategy is proposed, AR-Tri-training algorithm is designed by combining the rich information strategy. Finally, Classifiers are trained by using AR-Tri-training algorithm, and the integrated classifier is applied to voice detection. As can

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Singha, Anjani Kumar, Harsh Pratap Singh, Shakti Kundu, Pradeep Kumar Tiwari, and Ajeet Singh Rajput. "Estimating computer network security scenarios with association rules." Journal of Discrete Mathematical Sciences and Cryptography 27, no. 2 (2024): 223–36. http://dx.doi.org/10.47974/jdmsc-1876.

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Traditional NSSA (network security situational awareness) systems are problems familiarize to enormous for complicated network circumstances due to instrument limitations, inadequate and data fusion capabilities. This paper proposes the investigation of Association Rules (AR) based NSS (network security situation) prediction technology. Mining for regulations for associations to remedy this issue re- confidence support framework is enhanced by incorporating an interest. The assessment standard is revised, and the worth of AR is reassessed established on a discussion of associated standard idea

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Sun, Hongwei, Jiu Wang, Zhongwen Zhang, Naibao Hu, and Tong Wang. "An Efficient Algorithm for the Detection of Outliers in Mislabeled Omics Data." Computational and Mathematical Methods in Medicine 2021 (December 22, 2021): 1–11. http://dx.doi.org/10.1155/2021/9436582.

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High dimensionality and noise have made it difficult to detect related biomarkers in omics data. Through previous study, penalized maximum trimmed likelihood estimation is effective in identifying mislabeled samples in high-dimensional data with mislabeled error. However, the algorithm commonly used in these studies is the concentration step (C-step), and the C-step algorithm that is applied to robust penalized regression does not ensure that the criterion function is gradually optimized iteratively, because the regularized parameters change during the iteration. This makes the C-step algorith

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Vasquez-Jalpa, Carlos, Mariko Nakano, Martin Velasco-Villa, and Osvaldo Lopez-Garcia. "NRNH-AR: A Small Robotic Agent Using Tri-Fold Learning for Navigation and Obstacle Avoidance." Applied Sciences 15, no. 15 (2025): 8149. https://doi.org/10.3390/app15158149.

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We propose a tri-fold learning algorithm, called Neuroevolution of Hybrid Neural Networks in a Robotic Agent (acronym in Spanish, NRNH-AR), based on deep reinforcement learning (DRL), with self-supervised learning (SSL) and unsupervised learning (USL) steps, specifically designed to be implemented in a small autonomous navigation robot capable of operating in constrained physical environments. The NRNH-AR algorithm is designed for a small physical robotic agent with limited resources. The proposed algorithm was evaluated in four critical aspects: computational cost, learning stability, require

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Liu, Chang, Jie Zhang, Han Fang, Zehua Ma, Weiming Zhang, and Nenghai Yu. "DeAR: A Deep-Learning-Based Audio Re-recording Resilient Watermarking." Proceedings of the AAAI Conference on Artificial Intelligence 37, no. 11 (2023): 13201–9. http://dx.doi.org/10.1609/aaai.v37i11.26550.

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Audio watermarking is widely used for leaking source tracing. The robustness of the watermark determines the traceability of the algorithm. With the development of digital technology, audio re-recording (AR) has become an efficient and covert means to steal secrets. AR process could drastically destroy the watermark signal while preserving the original information. This puts forward a new requirement for audio watermarking at this stage, that is, to be robust to AR distortions. Unfortunately, none of the existing algorithms can effectively resist AR attacks due to the complexity of the AR proc

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Xu, Jianjian, and Dan Bai. "Multi-Objective Optimal Operation of the Inter-Basin Water Transfer Project Considering the Unknown Shapes of Pareto Fronts." Water 11, no. 12 (2019): 2644. http://dx.doi.org/10.3390/w11122644.

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Studies have shown that the performance of multi-objective evolutionary algorithms depends to a large extent on the shape of the Pareto fronts of the problem. Although, most existing algorithms have poor applicability in dealing with this problem, especially in the multi-objective optimization operation of reservoirs with unknown Pareto fronts. Therefore, this paper introduces an evolutionary algorithm with strong versatility and robustness named the Multi-Objective Evolutionary Algorithm with Reference Point Adaptation (AR-MOEA). In this paper, we take two water conservancy hubs (Huangjinxia

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Xue, Rixin, Peng Tang, and Shudong Fang. "Prediction of Computer Network Security Situation Based on Association Rules Mining." Wireless Communications and Mobile Computing 2022 (February 9, 2022): 1–9. http://dx.doi.org/10.1155/2022/2794889.

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Traditional NSSA (network security situational awareness) systems have significant equipment limitations, poor data fusion capabilities, and a low level of analysis and evaluation, making them difficult to adapt to large-scale and complex network environments. This paper proposes the study of computer NSS (network security situation) prediction technology based on AR (association rules) mining to solve this problem. The support-confidence framework is improved by introducing an interest evaluation standard, and the value of AR is re-evaluated, based on a discussion of traditional concepts and

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Nikolaev, A. A., and I. G. Gilemov. "Development and research of improved PWM algorithm of an active rectifier with variable switching angle tables." Vestnik IGEU, no. 6 (December 28, 2020): 48–56. http://dx.doi.org/10.17588/2072-2672.2020.6.048-056.

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Modern electric drives of rolling mills are based on frequency converters with active rectifiers (AR). During operation, active rectifiers consume non-sinusoidal current, having a negative effect on the supply network. In order to improve the performance index of voltage quality, AR special algorithms of pulse-width modulation are used. Selective harmonic elimination (SHE) PWM algorithm has become widespread. However, application of SHE PWM algorithm does not always allow to optimize the operation of the AR under the conditions of changing parameters of the electro-technical complex under vari

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Outahar, Mohamed, Guillaume Moreau, and Jean-Marie Normand. "Direct and Indirect vSLAM Fusion for Augmented Reality." Journal of Imaging 7, no. 8 (2021): 141. http://dx.doi.org/10.3390/jimaging7080141.

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Augmented reality (AR) is an emerging technology that is applied in many fields. One of the limitations that still prevents AR to be even more widely used relates to the accessibility of devices. Indeed, the devices currently used are usually high end, expensive glasses or mobile devices. vSLAM (visual simultaneous localization and mapping) algorithms circumvent this problem by requiring relatively cheap cameras for AR. vSLAM algorithms can be classified as direct or indirect methods based on the type of data used. Each class of algorithms works optimally on a type of scene (e.g., textured or

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Duan, Guiduo, Xiaotong Wang, Tianxi Huang, and Jürgen Kurths. "An Improved Group Similarity-Based Association Rule Mining Algorithm in Complex Scenes." International Journal of Pattern Recognition and Artificial Intelligence 34, no. 02 (2019): 2059005. http://dx.doi.org/10.1142/s0218001420590053.

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Association rule (AR) mining in complex scene has attracted extensive attention of researchers in recent years. Typically, many researchers focused on an algorithm itself and ignored a generalization method to improve the performance of AR mining. Tuna et al., presented a general data structure Speeding-Up AR Structure with Inverted Index Compression (SAII) which could be utilized in most of the existing algorithms to improve their performance IEEE Trans. Cybern. 46(12) (2016) 3059–3072. However, we found that this algorithm consumes a lot of time in re-ordering data because a one-to-one compa

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Jia, Teng Fei, Bo Zhu, You Xuan Zhao, and Han Ying Hu. "AR Prediction Model Based IMM Tracking Algorithm." Applied Mechanics and Materials 427-429 (September 2013): 632–35. http://dx.doi.org/10.4028/www.scientific.net/amm.427-429.632.

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In view of the problem of robust tracking of maneuvering target under LOS/NLOS condition, an IMM algorithm based on AR prediction model is proposed (ARIMM). First of all AR prediction model is adopted to model the motion state, and secondly UKF and RUKF are utilized separately for the reason that the state LOS and NLOS have different distribution of observation noise, and the IMM filter is used to estimate the position of BS, and finally the position is used to update the current parameters in AR prediction model and make the AR model more matched with the true motion state. Simulation result

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Chen, Juan, Zhengxuan Xue, and Dongxiao Han. "Dynamic multi-objective optimization for mixed traffic flow based on partial least squares prediction model." Journal of Algorithms & Computational Technology 13 (January 2019): 174830261987358. http://dx.doi.org/10.1177/1748302619873589.

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A dynamic multi-objective genetic algorithm based on partial least squares prediction model (DNSGA-II-PLS) is presented in this paper to solve the mix traffic flow multi-objective timing optimization problem with time-varying traffic demand. Take motor vehicle delay, non-motor vehicle delay, and pedestrian delay as objectives to solve the problem. Make comparison with three improved dynamic multi-objective genetic algorithms based on prediction strategy: dynamic multi-objective evolutionary algorithm based on simple prediction (DNSGA-II-PREM), autonomous regression dynamic multi-objective evol

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Nguyen, Linh, Htoo Thiri Htet, Yong-Ju Lee, and Man-Woo Park. "Augmented Reality Framework for Retrieving Information of Moving Objects on Construction Sites." Buildings 14, no. 7 (2024): 2089. http://dx.doi.org/10.3390/buildings14072089.

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The construction industry is undergoing a digital transformation, with the digital twin serving as a core system for project information. This digital twin provides an opportunity to utilize AR technology for real-time verification of on-site project information. Although many AR developments for construction sites have been attempted, they have been limited to accessing information on stationary components via Building Information Models. There have been no attempts to access information on dynamically changing resources, such as personnel and equipment. This paper addresses this gap by prese

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Chen, Jun, Bo Li, and Er Fei Wang. "Relaxed Parallel Scheduling Algorithms Investigation of Support Resource Reservation from Grid." Applied Mechanics and Materials 182-183 (June 2012): 1849–53. http://dx.doi.org/10.4028/www.scientific.net/amm.182-183.1849.

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In this paper, the grid computing environment resource reservation problem of using the parallel machine, proposed the relaxed time parallel scheduling models and algorithms support resource reservation. The simulation results of FCFS and EASY backfill algorithms in resource utilization, job bounded slowdown factor and the success rate of Advanced Reservation (AR) jobs were studied. Show that the relaxation mechanism, the average waiting time and the average bounded slowdown factor of non-reserved jobs down. EASY backfill algorithm which guarantees AR jobs quality of service at the same time,

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Koutitas, George, Varun Kumar Siddaraju, and Vangelis Metsis. "In Situ Wireless Channel Visualization Using Augmented Reality and Ray Tracing." Sensors 20, no. 3 (2020): 690. http://dx.doi.org/10.3390/s20030690.

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This article presents a novel methodology for predicting wireless signal propagation using ray-tracing algorithms, and visualizing signal variations in situ by leveraging Augmented Reality (AR) tools. The proposed system performs a special type of spatial mapping, capable of converting a scanned indoor environment to a vector facet model. A ray-tracing algorithm uses the facet model for wireless signal predictions. Finally, an AR application overlays the signal strength predictions on the physical space in the form of holograms. Although some indoor reconstruction models have already been deve

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Jiao, Liangbao, De Zhang, and Bi Houjie. "Differential AR algorithm for packet delay prediction*." Progress in Natural Science 16, no. 4 (2006): 437–40. http://dx.doi.org/10.1080/10020070612330016.

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Wang, Tie Sheng, Bing Zhang, and Kai Feng Ma. "Subsidence Monitoring Model of AR and Kalman Hybrid Algorithm and its Application." Advanced Materials Research 168-170 (December 2010): 2683–87. http://dx.doi.org/10.4028/www.scientific.net/amr.168-170.2683.

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The non-stationary time series data are dealt with the hybrid algorithm modal which combining the combined kalman and AR algorithm, and the modal was build, which the parameters stochastic variance of the AR modal was set in the state equations instead of extracting the tendency items from original data in conventional AR modals, and measure equations were constructed by observation data, then the AR modal can be solved by the Kalman algorithm. The deformation prediction results of the modal used in underground tunnel construction showed that this method was accuracy and feasible.

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Ji, Min, Jing Feng He, and You Qiang Lai. "AR Model Power Spectrum Estimation and MATLAB Simulation." Advanced Materials Research 971-973 (June 2014): 1561–64. http://dx.doi.org/10.4028/www.scientific.net/amr.971-973.1561.

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the power spectrum estimation researches various characteristics of signals in the frequency domain. The purpose is that signals are recognized and extract .Because these useful signals are submerged in noise .The article introduces estimation in the classic power spectrum and modern power spectrum. It is important that algorithm of AR model parameters are introduced in the parameter estimation of several typical. It discusses the advantages and disadvantages of various algorithms, and with the help of MATLAB platform, the various algorithms of power spectrum are simulated, in order to underta

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Zheng, Wei Xing. "Study of a least-squares-based algorithm for autoregressive signals subject to white noise." Mathematical Problems in Engineering 2003, no. 3 (2003): 93–101. http://dx.doi.org/10.1155/s1024123x03210012.

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A simple algorithm is developed for unbiased parameter identification of autoregressive (AR) signals subject to white measurement noise. It is shown that the corrupting noise variance, which determines the bias in the standard least-squares (LS) parameter estimator, can be estimated by simply using the expected LS errors when the ratio between the driving noise variance and the corrupting noise variance is known or obtainable in some way. Then an LS-based algorithm is established via the principle of bias compensation. Compared with the other LS-based algorithms recently developed, the introdu

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Yan, Hai’an, Jian Wang, and Peng Zhang. "Application of Optimized ORB Algorithm in Design AR Augmented Reality Technology Based on Visualization." Mathematics 11, no. 6 (2023): 1278. http://dx.doi.org/10.3390/math11061278.

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The current media digitization and artistic strength are more powerful than the previous application. Using its advanced information display methods and technologies, this paper proposed a digital museum built by integrating digital media art with AR technology, which was helpful to analyze and solve the objective problems of current museums’ ecological imbalance and single-system function. Based on the principles and laws of augmented reality technology, the museum guide system is optimized. In the system evaluation experiment, firstly, the cultural relics of six kinds of materials are used a

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Ivanov, Vladimir M., Anton M. Krivtsov, Anton Yu Smirnov, et al. "Experience in the Application of Augmented Reality Technology in the Surgical Treatment of Patients Suffering Primary and Recurrent Pelvic Tumors." Journal of Personalized Medicine 14, no. 1 (2023): 19. http://dx.doi.org/10.3390/jpm14010019.

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Surgical treatment of locally spread tumors in pelvic organs remains an urgent and complicated oncological problem. The recurrence rate after radical treatment ranges from 15.1% to 45.2%. The key to successful and safe surgical intervention lies in meticulous planning and intraoperative navigation, including the utilization of augmented reality (AR) technology. This paper presents the experience of clinically testing an AR technology application algorithm in the surgical treatment of 11 patients. The main stages of the algorithm are described. Radical operations incorporating intraoperative AR

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Hsieh, Chung-Hung, and Jiann-Der Lee. "Markerless Augmented Reality via Stereo Video See-Through Head-Mounted Display Device." Mathematical Problems in Engineering 2015 (2015): 1–13. http://dx.doi.org/10.1155/2015/329415.

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Conventionally, the camera localization for augmented reality (AR) relies on detecting a known pattern within the captured images. In this study, a markerless AR scheme has been designed based on a Stereo Video See-Through Head-Mounted Display (HMD) device. The proposed markerless AR scheme can be utilized for medical applications such as training, telementoring, or preoperative explanation. Firstly, a virtual model for AR visualization is aligned to the target in physical space by an improved Iterative Closest Point (ICP) based surface registration algorithm, with the target surface structure

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Wang, Yi-Han, Nathan W. C. Leigh, Bin Liu, and Rosalba Perna. "SpaceHub: A high-performance gravity integration toolkit for few-body problems in astrophysics." Monthly Notices of the Royal Astronomical Society 505, no. 1 (2021): 1053–70. http://dx.doi.org/10.1093/mnras/stab1189.

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ABSTRACT We present the open source few-body gravity integration toolkit SpaceHub. SpaceHub offers a variety of algorithmic methods, including the unique algorithms AR-Radau, AR-Sym6, AR-ABITS, and AR-chain+ which we show outperform other methods in the literature and allow for fast, precise, and accurate computations to deal with few-body problems ranging from interacting black holes to planetary dynamics. We show that AR-Sym6 and AR-chain+, with algorithmic regularization, chain algorithm, active round-off error compensation and a symplectic kernel implementation, are the fastest and most ac

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Zheng, Wei Xing. "Adaptive algorithm for noisy autoregressive signals." Mathematical Problems in Engineering 6, no. 6 (2001): 543–56. http://dx.doi.org/10.1155/s1024123x00001472.

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This paper presents a new type of improved least-squares (ILS) algorithm for adaptive parameter estimation of autoregressive (AR) signals from noisy observations. Unlike the previous ILS based methods, the developed algorithm can give consistent parameter estimates in a very direct manner that it does not involve dealing with an augmented noisy AR model. The new algorithm is demonstrated to outperform the previous ILS based methods in terms of its improved numerical efficiency.

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Xia, Zishuo, Zhiquan Feng, Xiaohui Yang, Dehui Kong, and Hong Cui. "MFIRA: Multimodal Fusion Intent Recognition Algorithm for AR Chemistry Experiments." Applied Sciences 13, no. 14 (2023): 8200. http://dx.doi.org/10.3390/app13148200.

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The current virtual system for secondary school experiments poses several issues, such as limited methods of operation for students and an inability of the system to comprehend the users’ operational intentions, resulting in a greater operational burden for students and hindering the goal of the experimental practice. However, many traditional multimodal fusion algorithms rely solely on individual modalities for the analysis of users’ experimental intentions, failing to fully utilize the intention information for each modality. To rectify these issues, we present a new multimodal fusion algori

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arman, Sup, Yahya Hairun, Idrus Alhaddad, Tedy Machmud, Hery Suharna, and Mohd Saifullah Rusiman. "Forecasting Software Using Laplacian AR Model based on Bootstrap-Reversible Jump MCMC: Application on Stock Price Data." Webology 18, Special Issue 04 (2021): 1045–55. http://dx.doi.org/10.14704/web/v18si04/web18180.

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The application of the Bootstrap-Metropolis-Hastings algorithm is limited to fixed dimension models. In various fields, data often has a variable dimension model. The Laplacian autoregressive (AR) model includes a variable dimension model so that the Bootstrap-Metropolis-Hasting algorithm cannot be applied. This article aims to develop a Bootstrap reversible jump Markov Chain Monte Carlo (MCMC) algorithm to estimate the Laplacian AR model. The parameters of the Laplacian AR model were estimated using a Bayesian approach. The posterior distribution has a complex structure so that the Bayesian e

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Mignolet, Marc P., and Pol D. Spanos. "Simulation of Homogeneous Two-Dimensional Random Fields: Part I—AR and ARMA Models." Journal of Applied Mechanics 59, no. 2S (1992): S260—S269. http://dx.doi.org/10.1115/1.2899499.

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The determination of autoregressive (AR) and autoregressive moving average (ARMA) algorithms for simulating realizations of two-dimensional random fields with a specified (target) power spectrum is examined. The form of both of these models is justified first by considering infinite-variate vector processes of appropriate spectral matrix. Next, the AR parameters are selected to achieve the minimum of a positive integral. Then, a technique is formulated to derive an ARM A simulation algorithm from the prior AR approximation by relying on the minimization of frequency domain errors. Finally, the

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Berezhanskiy, P. V., A. B. Malakhov, N. A. Geppe, N. G. Kolosova, and N. S. Tataurshchikova. "Diagnostics and preventive therapy of allergic rhinitis in children: modern algorithm." Russian Journal of Woman and Child Health 6, no. 3 (2023): 276–82. http://dx.doi.org/10.32364/2618-8430-2023-6-3-11.

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Background: allergic rhinitis (AR) is the leading pathology in pediatric practice. Improvement of the diagnostic accuracy and preventive measures in AR is the priority task. Aim: to evaluate the efficacy of the proposed cascade algorithm of diagnosis and preventive medicated therapy for children at high risk of AR. Patients and Methods: a retrospective epidemiological analysis was conducted in five regions of the Central Federal District for 2017–2021, where the main risk factors of AR were identified. The article proposes a screening cascade and a three-step diagnostic algorithm of AR, as wel

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Chen, Diyue, Hongyan Cui, and Roy E. Welsch. "An Adaptive Routing Algorithm Based on Relation Tree in DTN." Sensors 21, no. 23 (2021): 7847. http://dx.doi.org/10.3390/s21237847.

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It is found that nodes in Delay Tolerant Networks (DTN) exhibit stable social attributes similar to those of people. In this paper, an adaptive routing algorithm based on Relation Tree (AR-RT) for DTN is proposed. Each node constructs its own Relation Tree based on the historical encounter frequency, and will adopt different forwarding strategies based on the Relation Tree in the forwarding phase, so as to achieve more targeted forwarding. To further improve the scalability of the algorithm, the source node dynamically controls the initial maximum number of message copies according to its own

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Vedavathi, K., K. Srinivasa Rao, and A. Vinaya Babu. "Supervised learning algorithm with bivariate AR(p) model." International Journal of System Assurance Engineering and Management 5, no. 3 (2013): 205–12. http://dx.doi.org/10.1007/s13198-013-0143-z.

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Popov, E. "FEATURES OF THE USE OF AR TECHNOLOGIES IN THE FURNITURE BUSINESS." Actual directions of scientific researches of the XXI century: theory and practice 10, no. 3 (2022): 124–36. http://dx.doi.org/10.34220/2308-8877-2022-10-3-124-136.

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Digitalization has become the main catalyst for the development of all sectors of the economy of developed countries. The rapid growth of social networks has allowed the manufacturer to contact its consumer without intermediaries represented by large retailers. Internet commerce development trends consider AR and VR technologies as the most promising. In the Russian Federation, the AR/VR market, according to experts, by 2023 may increase by 11.7 times with an average annual growth rate of 85%. As a result of the analysis, the main problems of the AR market focused on the furniture segment were

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Li, Jihan, Xiaoli Li, and Kang Wang. "Atmospheric PM2.5Concentration Prediction Based on Time Series and Interactive Multiple Model Approach." Advances in Meteorology 2019 (October 15, 2019): 1–11. http://dx.doi.org/10.1155/2019/1279565.

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Urbanization, industrialization, and regional economic integration have developed rapidly in China in recent years. Air pollution has attracted more and more attention. However, PM2.5is the main particulate matter in air pollution. Therefore, how to predict PM2.5accurately and effectively has become a concern of experts and scholars. For the problem, atmosphere PM2.5concentration prediction algorithm is proposed based on time series and interactive multiple model in this paper. PM2.5concentration is collected by using the monitor at different air quality levels. The time series models are esta

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Wu, Yong, Weitao Che, and Bihui Huang. "An Improved 3D Registration Method of Mobile Augmented Reality for Urban Built Environment." International Journal of Computer Games Technology 2021 (February 10, 2021): 1–8. http://dx.doi.org/10.1155/2021/8810991.

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3D registration plays a pivotal role in augmented reality (AR) system. The existing methods are not suitable to be applied directly in the mobile AR system for the built environment, with the reasons of poor real-time performance and robustness. This paper proposes an improved 3D registration method of mobile AR for built environment, which is based on SURFREAK and KLT. This method increases the building efficiency of algorithm descriptors and maintains the robustness of the algorithms. To implement and evaluate the registration method, a smart phone-based mobile AR system for built environmen

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Liu, Xiyuan, Lingxiao Wang, Jiahao Li, Khan Raqib Mahmud, and Shuo Pang. "Enhancing Wildfire Detection via Trend Estimation Under Auto-Regression Errors." Mathematics 13, no. 7 (2025): 1046. https://doi.org/10.3390/math13071046.

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In recent years, global weather changes have underscored the importance of wildfire detection, particularly through Uncrewed Aircraft System (UAS)-based smoke detection using Deep Learning (DL) approaches. Among these, object detection algorithms like You Only Look Once version 7 (YOLOv7) have gained significant popularity due to their efficiency in identifying objects within images. However, these algorithms face limitations when applied to video feeds, as they treat each frame as an independent image, failing to track objects across consecutive frames. To address this issue, we propose a par

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Su, Wen Jun, and Hai Tao Chen. "A New Algorithm for Long-Term Estimation Based on AR Model." Applied Mechanics and Materials 614 (September 2014): 440–43. http://dx.doi.org/10.4028/www.scientific.net/amm.614.440.

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Traditional estimation methods have poor performance for long-term data forecast. Using Wiener model to estimate, power spectral density of the input signal, and cross-spectral density of the input and output signals are needed, that are difficult to obtain. And the large amount of calculation is needed using Wiener model. Using AR model and Kalman model, estimated results tend to mean of the training set while the estimated distance increases. For these cases, a new algorithm for long-term estimation based on AR model, named sampling AR model, is presented. Grouping the training set and using

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Chen, Zhi Qing, and You Shen Xia. "A Fast Algorithm for Vector ARMA Parameter Estimation." Advanced Materials Research 433-440 (January 2012): 4475–81. http://dx.doi.org/10.4028/www.scientific.net/amr.433-440.4475.

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In this paper, a fast algorithm for vector autoregressivemoving-average (ARMA) parameter estimation under noise environments is proposed. Based on an equivalent AR parameter model technique and a Yule-Walker equation technique, solving the parameter estimation problem of the VARMA model is well converted into solving linear equations. Therefore, the proposed algorithm has a lower computational complexity and a faster speed than conventional algorithms. Application examples with application to Lorenz systems confirm that the proposed algorithm can obtain a good solution.

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Huang, Kejia, Chenliang Wang, Runying Liu, and Guoxiong Chen. "A Fast and Accurate Spatial Target Snapping Method for 3D Scene Modeling and Mapping in Mobile Augmented Reality." ISPRS International Journal of Geo-Information 11, no. 1 (2022): 69. http://dx.doi.org/10.3390/ijgi11010069.

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High-performance spatial target snapping is an essential function in 3D scene modeling and mapping that is widely used in mobile augmented reality (MAR). Spatial data snapping in a MAR system must be quick and accurate, while real-time human–computer interaction and drawing smoothness must also be ensured. In this paper, we analyze the advantages and disadvantages of several spatial data snapping algorithms, such as the 2D computational geometry method and the absolute distance calculation method. To address the issues that existing algorithms do not adequately support 3D data snapping and rea

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Cui, Long Jie, Hong Li Wang, and Rong Yi Cui. "AR-Tri-Training: Tri-Training with Assistant Strategy." Applied Mechanics and Materials 513-517 (February 2014): 1840–44. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.1840.

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The classification performance of the classifier is weakened because the noise samples are introduced for the use of unlabeled samples in Tri-training. In this paper a new Tri-training style algorithm named AR-Tri-training (Tri-training with assistant and rich strategy) is proposed. Firstly, the assistant learning strategy is posed. Then the supporting learner is designed by combining the assistant learning strategy with rich information strategy. The number of mislabeled samples produced in the iterations of three classifiers mutually labeling are reduced by use of the supporting learner, mor

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Elfaladonna, Febie, Nita Novita, and Nyimas Rizki Amelia. "ANALISIS ALGORITMA C.45 PADA APLIKASI MONITORING KINERJA DAN PENCAPAIAN ACCOUNT REPRESENTATIVE DI KANTOR XYZ." Jurnal Sistem Informasi (JUSIN) 5, no. 1 (2024): 29–40. http://dx.doi.org/10.32546/jusin.v5i1.2530.

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Account Representative is a tax officer who is responsible for the implementation of services and direct supervision of a certain number of taxpayers who have been assigned as their responsibility. Monitoring account representative performance at XYZ Tax Office is less effective because performance and revenue data are updated and presented manually. To address this, the C4.5 Algorithm is proposed to support AR performance decision making. This algorithm forms a decision tree based on three main criteria: All AR Receipts, AR Receipts Per Person, and Target Receipts Per AR. The performance eval

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Vougas, Dimitrios V. "Prais–Winsten Algorithm for Regression with Second or Higher Order Autoregressive Errors." Econometrics 9, no. 3 (2021): 32. http://dx.doi.org/10.3390/econometrics9030032.

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There is no available Prais–Winsten algorithm for regression with AR(2) or higher order errors, and the one with AR(1) errors is not fully justified or is implemented incorrectly (thus being inefficient). This paper addresses both issues, providing an accurate, computationally fast, and inexpensive generic zig-zag algorithm.

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Rizaludin, Muhamad, Nur Hadian, and Nur Hayati. "INTEGRATING AUGMENTED REALITY WITH C4.5 ALGORITHM TO ENHANCE TOURISM EXPERIENCE IN PEKALONGAN." JITK (Jurnal Ilmu Pengetahuan dan Teknologi Komputer) 10, no. 4 (2025): 970–79. https://doi.org/10.33480/jitk.v10i4.6244.

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The tourism industry demands interactive and personalized solutions to enhance the traveler experience. However, providing relevant and customized travel recommendations based on individual preferences remains a challenge. This study integrates Augmented Reality (AR) technology with the C4.5 algorithm to address this issue and improve the tourism experience in Pekalongan Regency. The research method involved collecting data from 500 respondents through an online questionnaire. The collected data underwent preprocessing, including handling missing data, data transformation, and class balancing.

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Yang, Le, Shaobo Zhai, Guangwen Li, Mingshan Hou, and Qiuling Jia. "Generation of Guidance Commands for Civil Aircraft to Execute RNP AR Approach Procedure at High Plateau." Aerospace 10, no. 5 (2023): 396. http://dx.doi.org/10.3390/aerospace10050396.

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RNP AR is an operational procedure that uses the aircraft’s airborne navigation equipment and global positioning system to guide the aircraft to take off and land, and it is an effective means to ensure the flight safety of civil aircraft at high-plateau environments. In this paper, a three-dimensional, precise guidance command generation method for performing an RNP AR approach procedure is proposed. The lateral navigation transition paths between different segments are constructed, and a lateral segment switching strategy based on the angular bisector is introduced. To illustrate the availab

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Hsiaoping, Yeh. "Forecasting Personal Shopping Behavior." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 13, no. 2 (2014): 4146–56. http://dx.doi.org/10.24297/ijct.v13i2.2907.

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Data mining (DM) techniques make efforts to discovery knowledge from data. Aiming to finding patterns, association rule (AR) computing algorithms seem to be one to be adopted on variety applications. To be originally claimed for best analyzing customer shopping goods in baskets, Apriori, the first AR algorithm, has been discussed and modified the most by researchers. This study adopts Apriori algorithm to forecast individual customer shopping behavior. This study finds that customer shopping behaviors can be comprehended better in a long run. With Apriori mining and the examining principles pr

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Ding, Ke, and Ying Tan. "Attract-Repulse Fireworks Algorithm and its CUDA Implementation Using Dynamic Parallelism." International Journal of Swarm Intelligence Research 6, no. 2 (2015): 1–31. http://dx.doi.org/10.4018/ijsir.2015040101.

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Fireworks Algorithm (FWA) is a recently developed Swarm Intelligence Algorithm (SIA), which has been successfully used in diverse domains. When applied to complicated problems, many function evaluations are needed to obtain an acceptable solution. To address this critical issue, a GPU-based variant (GPU-FWA) was proposed to greatly accelerate the optimization procedure of FWA. Thanks to the active studies on FWA and GPU computing, many advances have been achieved since GPU-FWA. In this paper, a novel GPU-based FWA variant, Attract-Repulse FWA (AR-FWA), is proposed. AR-FWA introduces an efficie

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