Block-Based K-Medoids Partitioning Method with Standardized Data to Improve Clustering Accuracy by Kariyam, Kariyam, Abdurakhman, Abdurakhman, Subanar, Subanar, Utami, Herni, Effendie, Adhitya Ronnie

“…Most of the existing k-medoid algorithms select the initial medoid randomly or use a specific formula based on the proximity matrix. …”
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The Future of Cybersecurity in the Age of Quantum Computers by Fazal Raheman

“…Another one of the four post-quantum cryptography (PQC) algorithms selected by the NIST (National Institute of Standards and Technology) in a rigorous 5-year process was cracked by a team from Belgium. …”
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Secrecy Rate Analysis of Opportunistic User Scheduling in Uplink Networks With Potential Eavesdroppers by Inkyu Bang, Bang Chul Jung

“…The optimal user scheduling (OUS) algorithm selects the user who has the maximum secrecy rate, based on channel feedback from all users. …”
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A data-mining approach towards damage modelling for El Niño events in Peru by Fabio Brill, Silvia Passuni Pineda, Bruno Espichán Cuya, Heidi Kreibich

“…Besides the expected effect of precipitation, the classification algorithms select the topographic wetness index as most important feature, especially in low elevation areas. …”
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Emergency-Oriented Spatiotemporal Trajectory Pattern Recognition by Intelligent Sensor Devices by Ping Zhang, Qing Deng, Xiaodong Liu, Rui Yang, Hui Zhang

“…The sequential Monte Carlo method in conjunction with a state-transition model is employed to predict the updating real-time locations. The proposed algorithm selects particles from time-stamped sequential historical data sets. …”
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Muscle network topology analysis for the classification of chronic neck pain based on EMG biomarkers extracted during walking. by David Jiménez-Grande, S Farokh Atashzar, Eduardo Martinez-Valdes, Deborah Falla

“…With the use of Neighbourhood Component Analysis (NCA), we identified the most significant features and muscles for the classification/differentiation task conducted using K-Nearest Neighbourhood (K-NN), Support Vector Machine (SVM), and Linear Discriminant Analysis (LDA) algorithms. The NCA algorithm selected features from muscle network topology as one of the most relevant feature sets, which further emphasize the presence of major differences in muscle network topology between people with and without CNP. …”
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A tree search algorithm towards solving Ising formulated combinatorial optimization problems by Yunuo Cen, Debasis Das, Xuanyao Fong

“…At each iteration, the algorithm selects the best near-optimal solution within the feasible search space by exploring along the tree in the sense of “look ahead”. …”
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Application of Signal Denoising Technology Based on Improved Spectral Subtraction in Arc Fault Detection by Wenjia Wang, Jiacheng Li, Shouxiang Lu

“…According to the results of the arc fault detection algorithm, the algorithm selects an appropriate reference current as the basis for noise estimation and further assumes that the types and quantities of power loads are relatively fixed and the current noise is relatively stable in a certain power consumption period in the same power consumption place, so as to obtain the current noise in the current power consumption environment, and then uses improved spectral subtraction to realize the real-time noise reduction of current signals required by the arc fault detection algorithm. …”
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An Improved Parameter Identification Algorithm for the Friction Model of Electro-Hydraulic Servo Systems by Jian Liao, Fuming Zhou, Jianbo Zheng

“…To address these shortcomings, this paper proposes an improved adaptive genetic identification algorithm. The proposed algorithm selects evolutionary processes adaptively according to the population concentration in the initial stage of population evolution. …”
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OPriv: Optimizing Privacy Protection for Network Traffic by Louma Chaddad, Ali Chehab, Ayman Kayssi

“…Then, we provide OPriv, a practical and efficient algorithm to solve dynamically the non-linear programming (NLP) problem, using Cplex optimization. Our heuristic algorithm selects target applications to mutate to and the corresponding packet length, and subsequently decreases the security risks of statistical traffic analysis attacks. …”
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Adaptive R-Peak Detection Algorithm Based on Brown Exponential Smoothing Model by Zihao Hao, Xiaoming Zhang, Zhengxi Lai

“…Therefore, an adaptive threshold R-peak detection algorithm based on Brown’s exponential smoothing model is proposed in this paper. The algorithm selects features based on the morphological characteristics and occurrence law of R-peaks, updates the threshold parameters using the Brown exponential smoothing model, optimizes the smoothing coefficients in it using the relative error least squares method, corrects the smoothing ability of the observation error and the response speed to the change of the observation, so that the updated threshold can be more consistent with the R-peak detection. …”
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Dynamic Task Scheduling Algorithm with Deadline Constraint in Heterogeneous Volunteer Computing Platforms by Ling Xu, Jianzhong Qiao, Shukuan Lin, Wanting Zhang

“…For this situation, this paper proposes a dynamic task scheduling algorithm for heterogeneous VC with deadline constraint, called deadline preference dispatch scheduling (DPDS). The DPDS algorithm selects tasks with the nearest deadline each time and assigns them to volunteer nodes (VN), which solves the dynamic task scheduling problem with deadline constraint. …”
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Study on Big Graph Traversals for Storage Medium Optimization by JIAO Tianzhe, HE Hongyan, ZHANG Zexin, SONG Jie

“…As the basis of many algorithms,the breadth-first search(BFS) algorithm for big graph data has attracted more and more interests industrially and academically.Among the researches on BFS for the big graph,the solid state disk(SSD) is utilized to improve algorithm performance.In the graph traversal,the storage devices are required to continuously and repeatedly load data to fulfill the demand of graph traversal.However,many operations of data wipe caused by continuously and repeatedly loading data severely degrade the lifetime of SSD.For this reason,the lifetime of SSD can be effectively extended by reducing the data for write operations.Firstly,combined with the characteristics of graph structure,the data reuse model is constructed for describing the levels of data reuse in graph traversal.Then,a heuristic priority access algorithm based on vertex degree is proposed.By judging the independence of vertexes,the proposed algorithm selects graph vertexes that are priority accessed for improving the probability of data reusing,increasing hit ratio,and reducing the wear of flash memory.This method is available to any BFS algorithms and datasets without modifying BFS algorithm and big graph data.In the end,simulation results demonstrate that the proposed model and algorithm are effective.By applying the proposed algorithm on three common BFS algorithms:BFS-4K,B40C,and Gunrock,it can effectively reduce the operations of data written in graph traversal and improve the lifetime of SSD 12%,15%,22%,respectively.…”
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Climate-driven soil suction variation using a natural-order Fourier series approach by Olaiz Austin, Zapata Claudia

“…The NOFS incorporates an algorithmic selection criterion to optimize the order of the Fourier series to improve the capture of the seasonal shifts and extreme climate periods, while maintaining acceptable computation efficiency. …”
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Reinforcement Learning for Delay Tolerance and Energy Saving in Mobile Wireless Sensor Networks by Oday Al-Jerew, Nizar Al Bassam, Abeer Alsadoon

“…In particular, the proposed algorithm selects groups of CHs to receive sensing data of cluster nodes within a bounded hop count and forward the data to the mobile BS when it arrives. …”
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An Eccentricity Based Data Routing Protocol with Uniform Node Distribution in 3D WSN by A. S. M. Sanwar Hosen, Gi Hwan Cho, In-Ho Ra

“…At the same time, the routing algorithm selects a forwarding node in such a way that balances the energy consumption among RC nodes and reduces the number of hops towards the sink. …”
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Grey Wolf Optimizes Mixed Parameter Multi-Classification Twin Support Vector Machine by ZHOU Guangyue, LI Kewen, LIU Wenying, SU Zhaoxin

“…This paper proposes a multi-classification twin support vector machine based on mixed parameters (MP-MTWSVM). This algorithm selects appropriate parameters for different sub-classifiers, maintaining the diversity of classifiers, then constructing MTWSVM in terms of the “one-versus-one” strategy. …”
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The Delta Tree: An Object-Centered Approach to Image-Based Rendering by Dally, William J., McMillan, Leonard, Bishop, Gary, Fuchs, Henry

“…The rendering process generates an image at an arbitrary viewpoint by traversing the delta tree from a root node to one or more of its leaves. A subdivision algorithm selects only the required blocks from the nodes along the path. …”
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Image recognition using artificial intelligence(multi-object tracking using artificial intelligence) by Su, Hang

“…The baseline tracking algorithm selected was ByteTrack and BoT-SORT, which employs deep learning techniques to track objects over time by associating object detection bounding boxes across frames. …”
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Assessing short-term risk of ischemic stroke in relation to all prescribed medications by Imre Janszky, Ioannis Vardaxis, Bo Henry Lindqvist, Jens Wilhelm Horn, Ben Michael Brumpton, Linn Beate Strand, Inger Johanne Bakken, Ingvild Vatten Alsnes, Pål Richard Romundstad, Rickard Ljung, Kenneth Jay Mukamal, Abhijit Sen

“…Application of the Bolasso regression algorithm selected 19 drugs which were associated with increased risk for ischemic stroke and 11 drugs with decreased risk in both countries. …”
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