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Journal articles on the topic 'Proposed algorithm'

Author: Grafiati
Published: 4 June 2025
Last updated: 11 July 2025

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1

Ali, Nawafil Abdulwahab, and Imad Al Shaikhli. "Proposed De-noising Algorithm." International Journal on Perceptive and Cognitive Computing 6, no. 2 (2020): 90–96. http://dx.doi.org/10.31436/ijpcc.v6i2.164.

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minimizing noises from images to restore it and increase its quality is a crucial step. For this, an efficient algorithms were proposed to remove noises such as (salt pepper, Gaussian, and speckle) noises from grayscale images. The algorithm did that by selecting a window measuring 3x3 as the center of processing pixels, other algorithms did that by using median filter (MF), adopted median filter (AMF), adopted weighted filter (AWF), and the adopted weighted median filter (AWMF). The results showed that the proposed algorithm compares to previous algorithms by having a better signal-to-noise ratio (PSNR).
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Mohammed, Mohanad A., and Hala B. Abdul Wahab. "Proposed New Blockchain Consensus Algorithm." International Journal of Interactive Mobile Technologies (iJIM) 16, no. 20 (2022): 162–76. http://dx.doi.org/10.3991/ijim.v16i20.35549.

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Blockchain technology considers the central technology that is used within many applications used frequently with human life. And the primary core of the blockchain is the consensus algorithm which may affect the security of the chain as well as the required resource consumption which affect mainly the blockchain performance directly. In recent years many consensus algorithms have been used and proposed such as proof of work (PoW) and proof of stake (PoS) and many others. However, these algorithms still need some improvement to the security and system resource consumption which will reduce the need for a huge amount of energy and save the environment as well as let the blockchain be useable within low computation ability devices such as the internet of things devices (IoT). This paper proposes a new consensus algorithm that ensures the integrity and authorization of nodes participating in the validation of the transaction and only a predefined number of nodes chosen randomly to participate in block addition which reduces the need for high computations power for mining and voting. The proposed algorithm needs lower time and computation costs comparable to the standard POW algorithm.
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Shalaby, Wafaa, Waleed Saad, Mona Shokair, and Moawad Dessouky. "Modified Recovery Algorithms Using proposed algorithm for Compressive Sampling." Menoufia Journal of Electronic Engineering Research 26, no. 1 (2017): 1–20. http://dx.doi.org/10.21608/mjeer.2017.63112.

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Yeo, Tiong-Cheng, Fang Qin Goh, Yao Neng Teo, and Ching-Hui Sia. "Approach to bradyarrhythmias: A proposed algorithm." Annals of the Academy of Medicine, Singapore 52, no. 2 (2023): 96–99. http://dx.doi.org/10.47102/annals-acadmedsg.2022411.

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Bradyarrhythmias are commonly encountered in clinical practice. While there are several electrocardiographic criteria and algorithms for tachyarrhythmias, there is no algorithm for bradyarrhythmias to the best of our knowledge. In this article, we propose a diagnostic algorithm that uses simple concepts: (1) the presence or absence of P waves, (2) the relationship between the number of P waves and QRS complexes, and (3) the regularity of time intervals (PP, PR and RR intervals). We believe this straightforward, stepwise method provides a structured and thorough approach to the wide differential diagnosis of bradyarrhythmias, and in doing so, reduces misdiagnosis and mismanagement. Keywords: Arrhythmia, bradyarrhythmia, bradycardia, cardiology, electrocardiography
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Mohamed, Shereen Yousef, Mohamed Hamed N. Taha, Hesham N. Elmahdy, and Hany Harb. "A Proposed Load Balancing Algorithm Over Cloud Computing (Balanced Throttled)." International Journal of Recent Technology and Engineering (IJRTE) 10, no. 2 (2021): 28–33. http://dx.doi.org/10.35940/ijrte.b6101.0710221.

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Cloud computing refers to the services and applications that are accessible throughout the world from data centers. All services and applications are available online. Virtual machine migration is an important part of virtualization which is considered as essential part in cloud computing environment. Virtual Machine Migration means transferring a running Virtual Machine with all its applications and the operating system state as it is to target destination machine where it continues to run as if nothing happened. It makes balancing between servers. This improves the performance by redistributing the workload among available servers. There are many algorithms of load balancing classified into two types: static load balancing algorithms and dynamic load balancing algorithms. This paper presents the algorithm (Balanced Throttled Load Balancing Algorithm- BTLB). It compares the results of the BTLB with round robin algorithm, AMLB algorithm and throttled load balancing algorithm. The results of these four algorithms would be presented in this paper. The proposed algorithm shows the improvement in response time (75 µs). Cloud analyst simulator is used to evaluate the results. BTLB was developed and tested using Java.
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Shereen, Yousef Mohamed, Hamed N. Taha Mohamed, N. Elmahdy Hesham, and Mohamed Mohieddin Harb Hany. "A Proposed Load Balancing Algorithm Over Cloud Computing (Balanced Throttled)." International Journal of Recent Technology and Engineering (IJRTE) 10, no. 2 (2021): 28–33. https://doi.org/10.35940/ijrte.B6101.0710221.

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Cloud computing refers to the services and applications that are accessible throughout the world from data centers. All services and applications are available online. Virtual machine migration is an important part of virtualization which is considered as essential part in cloud computing environment. Virtual Machine Migration means transferring a running Virtual Machine with all its applications and the operating system state as it is to target destination machine where it continues to run as if nothing happened. It makes balancing between servers. This improves the performance by redistributing the workload among available servers. There are many algorithms of load balancing classified into two types: static load balancing algorithms and dynamic load balancing algorithms. This paper presents the algorithm (Balanced Throttled Load Balancing Algorithm- BTLB). It compares the results of the BTLB with round robin algorithm, AMLB algorithm and throttled load balancing algorithm. The results of these four algorithms would be presented in this paper. The proposed algorithm shows the improvement in response time (75 µs). Cloud analyst simulator is used to evaluate the results. BTLB was developed and tested using Java.
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El Hennawy, Hadia M. S., Alaa E. A. Omar, and Salah M. A. Kholaif. "LEA: Link Encryption Algorithm Proposed Stream Cipher Algorithm." Ain Shams Engineering Journal 6, no. 1 (2015): 57–65. http://dx.doi.org/10.1016/j.asej.2014.08.001.

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Deghbouch, Hicham, and Fatima Debbat. "Hybrid Bees Algorithm with Grasshopper Optimization Algorithm for Optimal Deployment of Wireless Sensor Networks." Inteligencia Artificial 24, no. 67 (2021): 18–35. http://dx.doi.org/10.4114/intartif.vol24iss67pp18-35.

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This work addresses the deployment problem in Wireless Sensor Networks (WSNs) by hybridizing two metaheuristics, namely the Bees Algorithm (BA) and the Grasshopper Optimization Algorithm (GOA). The BA is an optimization algorithm that demonstrated promising results in solving many engineering problems. However, the local search process of BA lacks efficient exploitation due to the random assignment of search agents inside the neighborhoods, which weakens the algorithm’s accuracy and results in slow convergence especially when solving higher dimension problems. To alleviate this shortcoming, this paper proposes a hybrid algorithm that utilizes the strength of the GOA to enhance the exploitation phase of the BA. To prove the effectiveness of the proposed algorithm, it is applied for WSNs deployment optimization with various deployment settings. Results demonstrate that the proposed hybrid algorithm can optimize the deployment of WSN and outperforms the state-of-the-art algorithms in terms of coverage, overlapping area, average moving distance, and energy consumption.
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Wang, Yi, and Kangshun Li. "A Lévy Flight-Inspired Random Walk Algorithm for Continuous Fitness Landscape Analysis." International Journal of Cognitive Informatics and Natural Intelligence 17, no. 1 (2023): 1–18. http://dx.doi.org/10.4018/ijcini.330535.

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Heuristic algorithms are effective methods for solving complex optimization problems. The optimal algorithm selection for a specific optimization problem is a challenging task. Fitness landscape analysis (FLA) is used to understand the optimization problem's characteristics and help select the optimal algorithm. A random walk algorithm is an essential technique for FLA in continuous search space. However, most currently proposed random walk algorithms suffer from unbalanced sampling points. This article proposes a Lévy flight-based random walk (LRW) algorithm to address this problem. The Lévy flight is used to generate the proposed random walk algorithm's variable step size and direction. Some tests show that the proposed LRW algorithm performs better in the uniformity of sampling points. Besides, the authors analyze the fitness landscape of the CEC2017 benchmark functions using the proposed LRW algorithm. The experimental results indicate that the proposed LRW algorithm can better obtain the structural features of the landscape and has better stability than several other RW algorithms.
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kaushik, Yogita, Anup Bhola, and C. K. Jha. "Proposed SKYMAX Load balancing Algorithm." International Journal of Private Cloud Computing Environment and Management 2, no. 1 (2015): 9–16. http://dx.doi.org/10.21742/ijpccem.2015.2.1.02.

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Benabbassi, Youssef, Hafid Haffaf, and Congduc Pham. "Proposed Algorithm for Surveillance Applications." International Journal of Computer Applications Technology and Research 3, no. 1 (2014): 24–28. http://dx.doi.org/10.7753/ijcatr0301.1005.

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He, Xiao Yuan, Xin Kang, Cho Jui Tay, Chenggen Quan, and Huai Min Shang. "Proposed algorithm for phase unwrapping." Applied Optics 41, no. 35 (2002): 7422. http://dx.doi.org/10.1364/ao.41.007422.

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Hoffmeister, Ellen. "Rheumatoid Arthritis Treatment Algorithm Proposed." Lippincottʼs Bone and Joint Newsletter 19, no. 2 (2013): 13–17. http://dx.doi.org/10.1097/01.bonej.0000426729.98284.9a.

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kadhiem Jabbar, Emad, and Waheed Abd Al-Kadhiem Salman. "Proposed Parallel Association Rules Algorithm." Engineering and Technology Journal 32, no. 1B (2014): 157–68. http://dx.doi.org/10.30684/etj.32.1b.18.

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15

Huang, Xiabao, Zailin Guan, and Lixi Yang. "An effective hybrid algorithm for multi-objective flexible job-shop scheduling problem." Advances in Mechanical Engineering 10, no. 9 (2018): 168781401880144. http://dx.doi.org/10.1177/1687814018801442.

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Genetic algorithm is one of primary algorithms extensively used to address the multi-objective flexible job-shop scheduling problem. However, genetic algorithm converges at a relatively slow speed. By hybridizing genetic algorithm with particle swarm optimization, this article proposes a teaching-and-learning-based hybrid genetic-particle swarm optimization algorithm to address multi-objective flexible job-shop scheduling problem. The proposed algorithm comprises three modules: genetic algorithm, bi-memory learning, and particle swarm optimization. A learning mechanism is incorporated into genetic algorithm, and therefore, during the process of evolution, the offspring in genetic algorithm can learn the characteristics of elite chromosomes from the bi-memory learning. For solving multi-objective flexible job-shop scheduling problem, this study proposes a discrete particle swarm optimization algorithm. The population is partitioned into two subpopulations for genetic algorithm module and particle swarm optimization module. These two algorithms simultaneously search for solutions in their own subpopulations and exchange the information between these two subpopulations, such that both algorithms can complement each other with advantages. The proposed algorithm is evaluated on some instances, and experimental results demonstrate that the proposed algorithm is an effective method for multi-objective flexible job-shop scheduling problem.
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Kantawong, Krittika, and Sakkayaphop Pravesjit. "An Enhanced ABC algorithm to Solve the Vehicle Routing Problem with Time Windows." ECTI Transactions on Computer and Information Technology (ECTI-CIT) 14, no. 1 (2020): 46–52. http://dx.doi.org/10.37936/ecti-cit.2020141.200016.

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This work proposes an enhanced artificial bee colony algorithm (ABC) to solve the vehicle routing problem with time windows (VRPTW). In this work, the fuzzy technique, scatter search method, and SD-based selection method are combined into the artificial bee colony algorithm. Instead of randomly producing the new solution, the scout randomly chooses the replacement solution from the abandoned solutions from the onlooker bee stage. Effective customer location networks are constructed in order to minimize the overall distance. The proposed algorithm is tested on the Solomon benchmark dataset where customers live in different geographical locations. The results from the proposed algorithm are shown in comparison with other algorithms in the literature. The findings from the computational results are very encouraging. Compared to other algorithms, the proposed algorithm produces the best result for all testing problem sets. More significantly, the proposed algorithm obtains better quality than the other algorithms for 39 of the 56 problem instances in terms of vehicle numbers. The proposed algorithm obtains a better number of vehicles and shorter distances than the other algorithm for 20 of the 39 problem instances.
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Shanmugapriya, S., and N. Priya. "The Proposed IT-TALB in Infrastructure as a Service Cloud." Indian Journal Of Science And Technology 17, no. 16 (2024): 1654–62. http://dx.doi.org/10.17485/ijst/v17i16.3274.

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Objectives: The purpose of the proposed IT-TALB load balancing algorithm is to dynamically allocate the user's workload to the appropriate virtual machine in an Infrastructure as a Service (IaaS) cloud environment. Methods: This research work includes several key procedures. The user's workloads are distributed to the data center controller (DCC), which in turn uses the ECO-SBP service broker policy to select the efficient data center (DC) for processing the loads. The DCC forwards the load to the selected DC, and the IT-TALB load balancer picks the best Virtual Machine (VM) using CloudAnalyst simulation tool for load allocations according to metrics such as its size, current number of loads, and load size. IT-TALB partitions the available and busy VMs separately and stores them in the TreeMap structure. This algorithm also incorporates the scalability of the given VM when the load size is not compatible with the existing VMs by extending the resources of underutilized VMs. Findings: The research finding demonstrates that the proposed IT-TALB algorithm improves IaaS cloud performance compared to the existing algorithms. It achieves optimum load balancing, reduces the searching time of the VM, avoids the load waiting time, improves throughput, minimizes the response time, and enhances the resource utilization ratio. IT-TALB yields a throughput and resource utilization ratio of 98 to 99 percent. Novelty: The novelty of this research is that the IT-TALB algorithm incorporates the scalability of the underutilized VM and also introduces new metrics such as throughput and resource utilization ratio in the CloudAnalyst simulation tool for assessing the performance of the proposed algorithm. This study provides information for analyzing the proposed IT-TALB strategies with the existing two algorithms such as TLB and TALB in order to show its performance. Keywords: Cloud Computing, Infrastructure as a Service, Load Balancing, Throttled Load Balancing, Virtual Machine
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Kang, Tae-Won, Jin-Gu Kang, and Jin-Woo Jung. "A Bidirectional Interpolation Method for Post-Processing in Sampling-Based Robot Path Planning." Sensors 21, no. 21 (2021): 7425. http://dx.doi.org/10.3390/s21217425.

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This paper proposes a post-processing method called bidirectional interpolation method for sampling-based path planning algorithms, such as rapidly-exploring random tree (RRT). The proposed algorithm applies interpolation to the path generated by the sampling-based path planning algorithm. In this study, the proposed algorithm is applied to the path created by RRT-connect and six environmental maps were used for the verification. It was visually and quantitatively confirmed that, in all maps, not only path lengths but also the piecewise linear shape were decreased compared to the path generated by RRT-connect. To check the proposed algorithm’s performance, visibility graph, RRT-connect algorithm, Triangular-RRT-connect algorithm and post triangular processing of midpoint interpolation (PTPMI) were compared in various environmental maps through simulation. Based on these experimental results, the proposed algorithm shows similar planning time but shorter path length than previous RRT-like algorithms as well as RRT-like algorithms with PTPMI having a similar number of samples.
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Ben Halima Abid, Donia, Saif Eddine Abouda, Hanane Medhaffar, and Mohamed Chtourou. "An Improved Method for Stochastic Nonlinear System’s Identification Using Fuzzy-Type Output-Error Autoregressive Hammerstein–Wiener Model Based on Gradient Algorithm, Multi-Innovation, and Data Filtering Techniques." Complexity 2021 (August 20, 2021): 1–29. http://dx.doi.org/10.1155/2021/8525090.

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This paper proposes an innovative identification approach of nonlinear stochastic systems using Hammerstein–Wiener (HW) model with output-error autoregressive (OEA) noise. Two fuzzy systems are suggested for the identification of the input and output nonlinear blocks of a proposed model from given input-output data measurements. In this work, the need for the commonly used assumptions including well-known structure of input and/or output nonlinearities and/or reversible nonlinear output is eliminated by replacing the intermediate variables and noise with their estimates. Four parametric estimation algorithms to identify the proposed fuzzy-type stochastic output-error autoregressive HW (FSOEAHW) model are derived based on backpropagation algorithm and multi-innovation and data filtering identification techniques. The proposed algorithms are improved backpropagation gradient (IBPG) algorithm, multi-innovation IBPG (MIIBPG) algorithm, a data filtering IBPG (FIBPG) algorithm, and a multi-innovation-based FIBPG (MIFIBPG) algorithm. The convergence of the parameter estimation algorithms is studied. The effectiveness of the proposed algorithms is shown by a given simulation example.
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Wu, Qing, Xudong Shen, Yuanzhe Jin, et al. "Intelligent Beetle Antennae Search for UAV Sensing and Avoidance of Obstacles." Sensors 19, no. 8 (2019): 1758. http://dx.doi.org/10.3390/s19081758.

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Based on a bio-heuristic algorithm, this paper proposes a novel path planner called obstacle avoidance beetle antennae search (OABAS) algorithm, which is applied to the global path planning of unmanned aerial vehicles (UAVs). Compared with the previous bio-heuristic algorithms, the algorithm proposed in this paper has advantages of a wide search range and breakneck search speed, which resolves the contradictory requirements of the high computational complexity of the bio-heuristic algorithm and real-time path planning of UAVs. Besides, the constraints used by the proposed algorithm satisfy various characteristics of the path, such as shorter path length, maximum allowed turning angle, and obstacle avoidance. Ignoring the z-axis optimization by combining with the minimum threat surface (MTS), the resultant path meets the requirements of efficiency and safety. The effectiveness of the algorithm is substantiated by applying the proposed path planning algorithm on the UAVs. Moreover, comparisons with other existing algorithms further demonstrate the superiority of the proposed OABAS algorithm.
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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 this paper can improve the lower cost of equipment to reflect the impact of the geographic information scene function in the attachment, thus optimising the use of AR technology in new media, and the combination of the two allows the dissemination of traditional culture to be enhanced in many ways.
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Elhossini, Ahmed, Shawki Areibi, and Robert Dony. "Strength Pareto Particle Swarm Optimization and Hybrid EA-PSO for Multi-Objective Optimization." Evolutionary Computation 18, no. 1 (2010): 127–56. http://dx.doi.org/10.1162/evco.2010.18.1.18105.

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This paper proposes an efficient particle swarm optimization (PSO) technique that can handle multi-objective optimization problems. It is based on the strength Pareto approach originally used in evolutionary algorithms (EA). The proposed modified particle swarm algorithm is used to build three hybrid EA-PSO algorithms to solve different multi-objective optimization problems. This algorithm and its hybrid forms are tested using seven benchmarks from the literature and the results are compared to the strength Pareto evolutionary algorithm (SPEA2) and a competitive multi-objective PSO using several metrics. The proposed algorithm shows a slower convergence, compared to the other algorithms, but requires less CPU time. Combining PSO and evolutionary algorithms leads to superior hybrid algorithms that outperform SPEA2, the competitive multi-objective PSO (MO-PSO), and the proposed strength Pareto PSO based on different metrics.
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Liu, Xinran, Zhongju Wang, Long Wang, Chao Huang, and Xiong Luo. "A Hybrid Rao-NM Algorithm for Image Template Matching." Entropy 23, no. 6 (2021): 678. http://dx.doi.org/10.3390/e23060678.

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This paper proposes a hybrid Rao-Nelder–Mead (Rao-NM) algorithm for image template matching is proposed. The developed algorithm incorporates the Rao-1 algorithm and NM algorithm serially. Thus, the powerful global search capability of the Rao-1 algorithm and local search capability of NM algorithm is fully exploited. It can quickly and accurately search for the high-quality optimal solution on the basis of ensuring global convergence. The computing time is highly reduced, while the matching accuracy is significantly improved. Four commonly applied optimization problems and three image datasets are employed to assess the performance of the proposed method. Meanwhile, three commonly used algorithms, including generic Rao-1 algorithm, particle swarm optimization (PSO), genetic algorithm (GA), are considered as benchmarking algorithms. The experiment results demonstrate that the proposed method is effective and efficient in solving image matching problems.
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Wang, Ying, and Guorui Li. "An Iterative Hard Thresholding Algorithm based on Sparse Randomized Kaczmarz Method for Compressed Sensing." International Journal of Computational Intelligence and Applications 17, no. 03 (2018): 1850015. http://dx.doi.org/10.1142/s1469026818500153.

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The paper proposes a novel signal reconstruction algorithm through substituting the gradient descent method in the iterative hard thresholding algorithm with a faster sparse randomized Kaczmarz method. By designing a series of gradually attenuated weights for the matrix rows whose indexes lie outside of the support set of the original sparse signal, we can focus the iterations on the effective support rows of the measurement matrix. The experiment results show that the proposed algorithm presents a faster convergence rate and more accurate reconstruction accuracy than the state-of-the-art algorithms. Meanwhile, the successful reconstruction probability of the proposed algorithm is higher than that of other algorithms. Moreover, the characteristics of the proposed signal reconstruction algorithm are also analyzed in detail through numerical experiments.
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Suzuki, Yuta, and Yuchi Kanzawa. "Tsallis Entropy-Regularized Fuzzy Classification Maximum Likelihood Clustering with a t-Distribution." Journal of Advanced Computational Intelligence and Intelligent Informatics 29, no. 2 (2025): 365–78. https://doi.org/10.20965/jaciii.2025.p0365.

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This study proposes a fuzzy clustering algorithm based on fuzzy classification maximum likelihood, t-distribution, and Tsallis entropy regularization. The proposed algorithm is shown to be a generalization of the two conventional algorithms, not only in the use of their objective functions, but also at their algorithmic level. The robustness of the proposed algorithm to outliers was confirmed in numerical experiments using an artificial dataset. In addition, experiments using 11 real datasets demonstrated the superiority of proposed algorithm in terms of the clustering accuracy.
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Jusman, Yessi, Siew Cheok Ng, and Khairunnisa Hasikin. "Performances of proposed normalization algorithm for iris recognition." International Journal of Advances in Intelligent Informatics 6, no. 2 (2020): 161. http://dx.doi.org/10.26555/ijain.v6i2.397.

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Iris recognition has very high recognition accuracy in comparison with many other biometric features. The iris pattern is not the same even right and left eye of the same person. It is different and unique. This paper proposes an algorithm to recognize people based on iris images. The algorithm consists of three stages. In the first stage, the segmentation process is using circular Hough transforms to find the region of interest (ROI) of given eye images. After that, a proposed normalization algorithm is to generate the polar images than to enhance the polar images using a modified Daugman’s Rubber sheet model. The last step of the proposed algorithm is to divide the enhance the polar image to be 16 divisions of the iris region. The normalized image is 16 small constant dimensions. The Gray-Level Co-occurrence Matrices (GLCM) technique calculates and extracts the normalized image’s texture feature. Here, the features extracted are contrast, correlation, energy, and homogeneity of the iris. In the last stage, a classification technique, discriminant analysis (DA), is employed for analysis of the proposed normalization algorithm. We have compared the proposed normalization algorithm to the other nine normalization algorithms. The DA technique produces an excellent classification performance with 100% accuracy. We also compare our results with previous results and find out that the proposed iris recognition algorithm is an effective system to detect and recognize person digitally, thus it can be used for security in the building, airports, and other automation in many applications.
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Chen, Zhenpeng, Yuanjie Zheng, Xiaojie Li, et al. "Interactive Trimap Generation for Digital Matting Based on Single-Sample Learning." Electronics 9, no. 4 (2020): 659. http://dx.doi.org/10.3390/electronics9040659.

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Image matting refers to the task of estimating the foreground of images, which is an important problem in image processing. Recently, trimap generation has attracted considerable attention because designing a trimap for every image is labor-intensive. In this paper, a two-step algorithm is proposed to generate trimaps. To use the proposed algorithm, users must only provide some clicks (foreground clicks and background clicks), which are employed as the input to generate a binary mask. One-shot learning technique achieves remarkable progress on semantic segmentation, we extend this technique to perform the binary mask prediction task. The mask is further used to predict the trimap using image dilation. Extensive experiments were performed to evaluate the proposed algorithm. Experimental results show that the trimaps generated using the proposed algorithm are visually similar to the user-annotated ones. Comparing with the interactive matting algorithms, the proposed algoritm is less labor-intensive than trimap-based matting algorithm and achieved more accuate results than scribble-based matting algorithm.
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Li, Tianyou, Sipei Zhao, Li Rao, et al. "Experimental study of a distributed active noise control system with multi-device nodes based on augmented diffusion strategy." Journal of the Acoustical Society of America 156, no. 5 (2024): 3246–59. http://dx.doi.org/10.1121/10.0034363.

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Recently, distributed active noise control (DANC) algorithms have been explored as a way to reduce computational complexity while ensuring system stability, thereby outperforming conventional centralized and decentralized algorithms. Most existing DANC algorithms assume that each node has only one pair of loudspeaker and microphone, limiting their flexibility in practical applications. In contrast, this paper proposes a DANC algorithm with general multi-device nodes based on the recently developed augmented diffusion strategy, allowing flexible and scalable ANC applications. A real-time distributed ANC system based on a multi-core digital signal processor platform is developed in order to compare the control performance of the proposed extended augmented diffusion algorithm with that of existing centralized, decentralized and augmented diffusion algorithms. Real-time experiments demonstrate that the proposed algorithm exhibits noise reduction performance consistent with that of the centralized algorithm while achieving lower global computational complexity and avoiding the system instability risk of the decentralized algorithm. Further, the new algorithm improves convergence speed and reduces the global communication cost compared to the previous augmented diffusion algorithm. Experimental results indicate the application potential of the proposed DANC algorithm for a generalized system configuration.
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Jamshidi, Mojtaba, Milad Ranjbari, Mehdi Esnaashari, Nooruldeen Nasih Qader, and Mohammad Reza Meybodi. "Sybil Node Detection in Mobile Wireless Sensor Networks Using Observer Nodes." JOIV : International Journal on Informatics Visualization 2, no. 3 (2018): 159. http://dx.doi.org/10.30630/joiv.2.3.131.

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Sybil attack is one of the well-known dangerous attacks against wireless sensor networks in which a malicious node attempts to propagate several fabricated identities. This attack significantly affects routing protocols and many network operations, including voting and data aggregation. The mobility of nodes in mobile wireless sensor networks makes it problematic to employ proposed Sybil node detection algorithms in static wireless sensor networks, including node positioning, RSSI-based, and neighbour cooperative algorithms. This paper proposes a dynamic, light-weight, and efficient algorithm to detect Sybil nodes in mobile wireless sensor networks. In the proposed algorithm, observer nodes exploit neighbouring information during different time periods to detect Sybil nodes. The proposed algorithm is implemented by J-SIM simulator and its performance is compared with other existing algorithm by conducting a set of experiments. Simulation results indicate that the proposed algorithm outperforms other existing methods regarding detection rate and false detection rate. Moreover, they also showed that the mean detection rate and false detection rate of the proposed algorithm are respectively 99% and less than 2%.
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Sarasiri, Nuapett, Kittiwong Suthamno, and Sarawut Sujitjorn. "Bacterial Foraging-Tabu Search Metaheuristics for Identification of Nonlinear Friction Model." Journal of Applied Mathematics 2012 (2012): 1–23. http://dx.doi.org/10.1155/2012/238563.

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This paper proposes new metaheuristic algorithms for an identification problem of nonlinear friction model. The proposed cooperative algorithms are formed from the bacterial foraging optimization (BFO) algorithm and the tabu search (TS). The paper reports the search comparison studies of the BFO, the TS, the genetic algorithm (GA), and the proposed metaheuristics. Search performances are assessed by using surface optimization problems. The proposed algorithms show superiority among them. A real-world identification problem of the Stribeck friction model parameters is presented. Experimental setup and results are elaborated.
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Lee, Hae-In, Hyo-Sang Shin, and Antonios Tsourdos. "A Probabilistic–Geometric Approach for UAV Detection and Avoidance Systems." Sensors 22, no. 23 (2022): 9230. http://dx.doi.org/10.3390/s22239230.

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This paper proposes a collision avoidance algorithm for the detection and avoidance capabilities of Unmanned Aerial Vehicles (UAVs). The proposed algorithm aims to ensure minimum separation between UAVs and geofencing with multiple no-fly zones, considering the sensor uncertainties. The main idea is to compute the collision probability and to initiate collision avoidance manoeuvres determined by the differential geometry concept. The proposed algorithm is validated by both theoretical and numerical analysis. The results indicate that the proposed algorithm ensures minimum separation, efficiency, and scalability compared with other benchmark algorithms.
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Wang, Yu Ze, Shao Chuan Wu, and Wen Cui. "Gossip Algorithms for Average Energy Estimation in Wireless Sensor Networks." Applied Mechanics and Materials 577 (July 2014): 908–12. http://dx.doi.org/10.4028/www.scientific.net/amm.577.908.

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Gossip algorithms which belong to a kind of distributed algorithms can be used to compute the (possibly weighted) average of the initial measurements of the nodes at every node in the network. This paper proposes an improved broadcast gossip algorithm to estimate average energy with better accuracy. In this proposed algorithm, we use some companion variables to save the sum, and convergence error is decreasing with the number of companion variables increasing. Convergence of the proposed algorithm is studied theoretically and verified by simulations. Although the estimated value is random, we show that the novel algorithm can converge closer to average than broadcast gossip algorithm in probability.
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Peng, Xuesheng, Ruizhi Chen, Kegen Yu, Feng Ye, and Weixing Xue. "An Improved Weighted K-Nearest Neighbor Algorithm for Indoor Localization." Electronics 9, no. 12 (2020): 2117. http://dx.doi.org/10.3390/electronics9122117.

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The weighted K-nearest neighbor (WKNN) algorithm is the most commonly used algorithm for indoor localization. Traditional WKNN algorithms adopt received signal strength (RSS) spatial distance (usually Euclidean distance and Manhattan distance) to select reference points (RPs) for position determination. It may lead to inaccurate position estimation because the relationship of received signal strength and distance is exponential. To improve the position accuracy, this paper proposes an improved weighted K-nearest neighbor algorithm. The spatial distance and physical distance of RSS are used for RP selection, and a fusion weighted algorithm based on these two distances is used for position calculation. The experimental results demonstrate that the proposed algorithm outperforms traditional algorithms, such as K-nearest neighbor (KNN), Euclidean distance-based WKNN (E-WKNN), and physical distance-based WKNN (P-WKNN). Compared with the KNN, E-WKNN, and P-WKNN algorithms, the positioning accuracy of the proposed method is improved by about 29.4%, 23.5%, and 20.7%, respectively. Compared with some recently improved WKNN algorithms, our proposed algorithm can also obtain a better positioning performance.
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Ababneh, Jehad. "Greedy particle swarm and biogeography-based optimization algorithm." International Journal of Intelligent Computing and Cybernetics 8, no. 1 (2015): 28–49. http://dx.doi.org/10.1108/ijicc-01-2014-0003.

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Purpose – The purpose of this paper is to propose an algorithm that combines the particle swarm optimization (PSO) with the biogeography-based optimization (BBO) algorithm. Design/methodology/approach – The BBO and the PSO algorithms are jointly used in to order to combine the advantages of both algorithms. The efficiency of the proposed algorithm is tested using some selected standard benchmark functions. The performance of the proposed algorithm is compared with that of the differential evolutionary (DE), genetic algorithm (GA), PSO, BBO, blended BBO and hybrid BBO-DE algorithms. Findings – Experimental results indicate that the proposed algorithm outperforms the BBO, PSO, DE, GA, and the blended BBO algorithms and has comparable performance to that of the hybrid BBO-DE algorithm. However, the proposed algorithm is simpler than the BBO-DE algorithm since the PSO does not have complex operations such as mutation and crossover used in the DE algorithm. Originality/value – The proposed algorithm is a generic algorithm that can be used to efficiently solve optimization problems similar to that solved using other popular evolutionary algorithms but with better performance.
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Tu, Anqi, Chuang Shi, and Huiyong Li. "Convex combination of online secondary path modeling and improved cuckoo search for active noise control." INTER-NOISE and NOISE-CON Congress and Conference Proceedings 268, no. 6 (2023): 2172–79. http://dx.doi.org/10.3397/in_2023_0320.

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This paper proposes an active noise control (ANC) algorithm based on convex combination of the online secondary path modeling (OSPM) and improved cuckoo search (ICS) algorithms. The ICS algorithm does not request the secondary path model to optimize the control filter. Therefore, the ICS algorithm is theoretically not affected by a varying secondary path, but its convergence is very slow. In contrast, the OSPM algorithm achieves faster convergence but is vulnerable to a sudden change in the secondary path. The proposed ANC algorithm combines the merits of both the OSPM and ICS algorithms by convex combination. Simulation results show that the proposed ANC algorithm can achieve better performance than the conventional ANC algorithm especially when the secondary path changes drastically.
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Bechouat, Mohcene. "Proposed Algorithm MPPT for Photovoltaic System." International Journal of Energetica 3, no. 1 (2018): 10. http://dx.doi.org/10.47238/ijeca.v3i1.60.

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A proposed algorithm MPPT (Maximum Power Point Tracking) is proposed in this paper. When the insolation change rapidly, the P&O (Perturb and Observe) algorithm is used to adjust the operating point of the PV (Photovoltaic) array close to the MPP (Maximum Power Point) for fast tracking; also, the INC (Incremental Conductance) algorithm and the fuzzy controller skip drawbacks of the P&O algorithm by decreasing oscillations around the MPP and the underestimated. In addition, to improve the control precision, the effectiveness of proposed algorithm is validated by simulation using Matlab/Simulink, the simulation results show that the proposed algorithm tracks the MPP quickly, reduces the oscillation around the MPP effectively and improves the energy conversion efficiency of the PV panel.
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Malhotra, Ankit, Dipit Malhotra, and Saksham Kashyap. "Optimized Proposed Algorithm for Graph Traversal." International Journal of Computer Applications 104, no. 9 (2014): 38–43. http://dx.doi.org/10.5120/18234-9217.

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Herrera-Perez, Mario, David González-Martín, and Ramón Viladot-Pericé. "Proposed treatment algorithm for hallux rigidus." Journal of the Foot & Ankle 15, no. 3 (2021): 205–7. http://dx.doi.org/10.30795/jfootankle.2021.v15.1578.

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This study performs a literature review on the treatment of hallux rigidus and proposes a treatment algorithm.This literature systematic review expanded a similar study conducted in 2014 by the authors and analyzed the levels of recommendation according to scientific evidence.Most articles found in the search present scarce evidence (level IV or case series), we only found 8 articles with an at least moderate level of recommendation (B); of these, only one article had a level of evidence I.Conservative treatment is effective with the implementation of footwear modifications, use of insoles, and infiltrations with hyaluronic acid. Cheilectomy, either isolated or combined with Moberg osteotomy, shows good outcomes in stage III, or moderate, although its outcomes worsen after 5 years. Metatarsophalangeal joint (MTPJ) arthrodesis is still the gold standard in stage IV, or advanced. In recent years, the technique of interposition arthroplasty has re-emerged, especially with the use of a synthetic cartilage implant (Cartiva®), with outcomes at least similar to those of MTPJ arthrodesis in comparative studies. Level of Evidence III; Therapeutic Studies; Systematic Review of Level III Studies.
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Frigon, Jean-Yves, and Louis Laurencelle. "Analysis of Covariance: A Proposed Algorithm." Educational and Psychological Measurement 53, no. 1 (1993): 1–18. http://dx.doi.org/10.1177/0013164493053001001.

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BRUNK, DOUG. "Diagnostic Algorithm Proposed For Pulmonary Hypertension." Internal Medicine News 42, no. 15 (2009): 30. http://dx.doi.org/10.1016/s1097-8690(09)70589-x.

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Hart, Alexander, Michelangelo Bortolin, Oluwafunbi Awoniyi, Fahad Alhajjaj, and Gregory R. Ciottone. "A Proposed COVID-19 Testing Algorithm." Disaster Medicine and Public Health Preparedness 14, no. 5 (2020): e11-e15. http://dx.doi.org/10.1017/dmp.2020.218.

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ABSTRACTThe 2019 coronavirus disease (COVID-19) pandemic has led to physical distancing measures in numerous countries in an attempt to control the spread. However, these measures are not without cost to the health and economies of the nations in which they are enacted. Nations are now looking for methods to remove physical distancing measures and return to full functioning. To prevent a massive second wave of infections, this must be done with a data-driven methodology. The purpose of this article is to propose an algorithm for COVID-19 testing that would allow for physical distancing to be scaled back in a stepwise manner, which limits ensuing infections and protects the capacity of the health care system.
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Oosthuizen, J. C., P. Burns, and J. D. Russell. "Lymphatic malformations: A proposed management algorithm." International Journal of Pediatric Otorhinolaryngology 74, no. 4 (2010): 398–403. http://dx.doi.org/10.1016/j.ijporl.2010.01.013.

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Habib, Maan. "Proposed Algorithm of Land Parcel Subdivision." Journal of Surveying Engineering 146, no. 3 (2020): 04020012. http://dx.doi.org/10.1061/(asce)su.1943-5428.0000322.

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Lalanne, Ph, J. Taboury, and P. Chavel. "A proposed generalization of Hopfield's algorithm." Optics Communications 63, no. 1 (1987): 21–25. http://dx.doi.org/10.1016/0030-4018(87)90215-x.

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Bagnis, Alessandro, Carlo Alberto Cutolo, Guido Corallo, Donatella Musetti, Massimo Nicolò, and Carlo Enrico Traverso. "Chorioretinal folds: a proposed diagnostic algorithm." International Ophthalmology 39, no. 11 (2019): 2667–73. http://dx.doi.org/10.1007/s10792-019-01083-y.

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S. Rahma, Abdul-Monem, and Suhad AbdulZahra Hassan Al-Quraishi. "Kangaroo A Proposed Stream Cipher Algorithm." Engineering and Technology Journal 28, no. 3 (2010): 537–51. http://dx.doi.org/10.30684/etj.28.3.12.

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Jairaj, Chaitra, Gertrude Seneviratne, Veerle Bergink, Iris E. Sommer, and Paola Dazzan. "Postpartum Psychosis: A Proposed Treatment Algorithm." FOCUS 22, no. 1 (2024): 131–42. http://dx.doi.org/10.1176/appi.focus.23021033.

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BRUNK, DOUG. "Simple Algorithm Proposed For Pulmonary Hypertension." Cardiology News 7, no. 9 (2009): 14. https://doi.org/10.1016/s1544-8800(09)70220-9.

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Pranav, Bhokardankar* Harshal Sharma. "PROPOSED ALGORITHM FOR LOAD BALANCING ON CLOUD DATA CENTER." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 5, no. 12 (2016): 702–5. https://doi.org/10.5281/zenodo.218895.

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Cloud servers are basically developed for supporting the efficient communication and the computation remotely. Thus a number of different time zone machines are able to find the services of resources and the computation. Thus each and every time these machines are working in order to resolve the end client request. But sometime these machines are loaded more then their capacity and does not perform as desired and some of the available processing units are considered to be free. This results in the performance loss in the computational servers. In order to find the optimum performance there is need to implement some technique for load balancing. Thus in this presented work the key focus is placed on the investigation of load balancing approaches and the algorithm. In order to find the optimum technique of load balancing, various different algorithms are studied. Among them four most promising techniques are selected which are promising for load balancing in previous studies. These techniques are genetic algorithm which provides the optimization technique for finding most appropriate solution among available solutions, ABC (artificial honey bee colony) algorithm which is also an optimization technique in the similar ways, the round robin which is frequently used for process allocation during CPU scheduling and finally the self-organizing map which is an unsupervised class of machine learning. These methods are implemented and compared on the basis of their performance parameters. The implementation of the proposed comparative study is performed on the JAVA technology and using the Cloud Sim simulator. After simulation of the presented comparative study the performance of the SOM algorithm provides the optimum results as compared to the Genetic algorithm, Honey bee colony and RR (round robin) algorithms.
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Chen, Hao, Weikun Li, and Weicheng Cui. "Disruption-Based Multiobjective Equilibrium Optimization Algorithm." Computational Intelligence and Neuroscience 2020 (November 30, 2020): 1–21. http://dx.doi.org/10.1155/2020/8846250.

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Nature-inspired computing has attracted huge attention since its origin, especially in the field of multiobjective optimization. This paper proposes a disruption-based multiobjective equilibrium optimization algorithm (DMOEOA). A novel mutation operator named layered disruption method is integrated into the proposed algorithm with the aim of enhancing the exploration and exploitation abilities of DMOEOA. To demonstrate the advantages of the proposed algorithm, various benchmarks have been selected with five different multiobjective optimization algorithms. The test results indicate that DMOEOA does exhibit better performances in these problems with a better balance between convergence and distribution. In addition, the new proposed algorithm is applied to the structural optimization of an elastic truss with the other five existing multiobjective optimization algorithms. The obtained results demonstrate that DMOEOA is not only an algorithm with good performance for benchmark problems but is also expected to have a wide application in real-world engineering optimization problems.
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