Fixed-Time Synchronization for Different Dimensional Complex Network Systems with Unknown Parameters via Adaptive Control by Yude Ji, Yunli Gong, Shan Su, Xiaoxue Bai

“…Finally, a numerical example is given to illustrate the effectiveness of the proposed control algorithms.…”
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D3D-MDS: A Distributed 3D Localization Scheme for an Irregular Wireless Sensor Network Using Multidimensional Scaling by Jin Fan, Baohui Zhang, Guojun Dai

“…This paper proposes a distributed localization algorithm which can be applied to an irregular three-dimensional wireless sensor network, considering the algorithm accuracy and complexity. …”
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Existence of Solution and Self-Exciting Attractor in the Fractional-Order Gyrostat Dynamical System by Muhammad Marwan, Gauhar Ali, Ramla Khan

“…Moreover, this iterative scheme is injected into algorithms for a system of integer order dynamical systems to observe Lyapunov exponents and a bifurcation diagram for our proposed fractional-order dynamical model. …”
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Using WPCA and EWMA Control Chart to Construct a Network Intrusion Detection Model by Ying-Ti Tsai, Chung-Ho Wang, Yung-Chia Chang, Lee-Ing Tong

“…Artificial intelligence algorithms and big data analysis methods are commonly employed in network intrusion detection systems. …”
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Consensus Information Filtering for Large-Scale Systems with Application to Heat Conduction Process by Liguo Zhang, Ying Lyu

“…On diffusion processing, we fuse the common state estimations of the local information filters using consensus averaging algorithms and algebraic graph theory. Stability and performance analysis is provided for this distributed filtering algorithm. …”
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Differential Evolution without the Scale Factor and the Crossover Probability by Xiaowei Zhang

“…Numerical experiments show that the proposed algorithm outperforms the other 5 compared algorithms for the 10 benchmark functions.…”
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Challenges and opportunities for agricultural development in West Africa by P. Kamara

“…The task is to find, identify, develop and implement the most effective methods and algorithms for realising the above aim, and the challenges and obstacles along the way. …”
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Transit Route Network Design for Low-Mobility Individuals Using a Hybrid Metaheuristic Approach by Tao Zhang, Gang Ren, Yang Yang

“…Then, a hybrid metaheuristic approach based on ant colony and genetic algorithms is formulated to solve the proposed model in accordance with current conditions (i.e., existing routes that may need to undergo configuration adjustments to different degrees). …”
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Threshold Accepting Heuristic for Fair Flow Optimization in Wireless Mesh Networks by Jarosław Hurkała, Tomasz Śliwiński

“…Developing effective, fairness-preserving optimization algorithms is of considerable importance in systems which serve many users. …”
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An optimal adaptive time-stepping scheme for solving reaction-diffusion-chemotaxis systems by Chichia Chiu, Jui-Ling Yu

“…Theorems about stability and convergence of thealgorithm are given to show that the algorithm is highly stable and efficient.Numerical experiment results on a model problem are given for comparisonwith other numerical methods. …”
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Energy-Efficiency Maximization in Backscatter Communication-Based Non-Orthogonal Multiple Access System: Dinkelbach and Successive Convex Approximation Approaches by Dingjia Lin, Tianqi Wang, Kaidi Wang, Zhiguo Ding

“…The goal is to maximize energy efficiency (EE) through the optimization of the beamforming matrix and the reflection coefficient of the BackCom devices. Two algorithms, Dinkelbach based on penalty semidefinite relaxation (SDR) and successive convex approximation (SCA), are proposed as high-performance and low-complexity solutions, respectively. …”
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Identification and Analysis of Key Immune- and Inflammation-Related Genes in Idiopathic Pulmonary Fibrosis by Tan Y, Qian B, Ma Q, Xiang K, Wang S

“…Three genes (RNASE3, S100A12, S100A8) were obtained by crossing two machine algorithms (Boruta and LASSO),which had good diagnostic performance with AUC values. …”
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A Novel CGM Metric-Gradient and Combining Mean Sensor Glucose Enable to Improve the Prediction of Nocturnal Hypoglycemic Events in Patients with Diabetes by Jingzhen Li, Xiaojing Ma, Igbe Tobore, Yuhang Liu, Abhishek Kandwal, Lei Wang, Jingyi Lu, Wei Lu, Yuqian Bao, Jian Zhou, Zedong Nie

“…In addition, the prediction was conducted by four algorithms, namely, logistic regression, support vector machine, random forest, and long short-term memory. …”
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Predicting Treatment Outcomes in Patients with Low Back Pain Using Gene Signature-Based Machine Learning Models by Youzhi Lian, Yinyu Shi, Haibin Shang, Hongsheng Zhan

“…These key genes were then used to train 45 machine learning models by combining nine different algorithms: Logistic Regression, K-Nearest Neighbors, Support Vector Machine, Decision Tree, Random Forest, Gradient Boosting Machine, Multilayer Perceptron, Naive Bayes, and Linear Discriminant Analysis. …”
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Ion suppression correction and normalization for non-targeted metabolomics by Iqbal Mahmud, Bo Wei, Lucas Veillon, Lin Tan, Sara Martinez, Bao Tran, Alexander Raskind, Felice de Jong, Yiwei Liu, Jibin Ding, Yun Xiong, Wai-kin Chan, Rehan Akbani, John N. Weinstein, Chris Beecher, Philip L. Lorenzi

“…Here we report a method, the IROA TruQuant Workflow, that uses a stable isotope-labeled internal standard (IROA-IS) library plus companion algorithms to: 1) measure and correct for ion suppression, and 2) perform Dual MSTUS normalization of MS metabolomic data. …”
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Bi-level data-driven enterprise-wide optimization with mixed-integer nonlinear scheduling problems by Hasan Nikkhah, Zahir Aghayev, Amir Shahbazi, Vassilis M. Charitopoulos, Styliani Avraamidou, Burcu Beykal

“…Nonetheless, the bi-level optimization of such interdependent and holistic formulations is still difficult, particularly when dealing with mixed-integer nonlinear programming (MINLP) problems, due to a lack of effective algorithms. In this study, we employ the Data-driven Optimization of bi-level Mixed-Integer NOnlinear problems (DOMINO) framework, a data-driven algorithm developed to handle single-leader single-follower bi-level mixed-integer problems, to solve single-leader multi-follower planning and scheduling problems subject to MINLP scheduling formulations. …”
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AIPerf: Automated Machine Learning as an AI-HPC Benchmark by Zhixiang Ren, Yongheng Liu, Tianhui Shi, Lei Xie, Yue Zhou, Jidong Zhai, Youhui Zhang, Yunquan Zhang, Wenguang Chen

“…The plethora of complex Artificial Intelligence (AI) algorithms and available High-Performance Computing (HPC) power stimulates the expeditious development of AI components with heterogeneous designs. …”
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Enhancing Semi-Supervised Learning With Concept Drift Detection and Self-Training: A Study on Classifier Diversity and Performance by Jose L. M. Perez, Roberto S. M. Barros, Silas G. T. C. Santos

“…Machine learning algorithms that assist in decision-making are becoming crucial in several areas, such as healthcare, finance, marketing, etc. …”
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StrideHD: A Binary Hyperdimensional Computing System Utilizing Window Striding for Image Classification by Dehua Liang, Jun Shiomi, Noriyuki Miura, Hiromitsu Awano

“…Our evaluation also shows that compared with two popular HD algorithms, the singlepass StrideHD model achieves a 27.6<inline-formula> <tex-math notation="LaTeX">$\times$ </tex-math></inline-formula> and 8.2<inline-formula> <tex-math notation="LaTeX">$\times$ </tex-math></inline-formula> reduction in inference memory cost without hurting the classification accuracy, while the iterative mode further provides 8.7<inline-formula> <tex-math notation="LaTeX">$\times$ </tex-math></inline-formula> memory efficiency. …”
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Ensemble learning to predict short birth interval among reproductive-age women in Ethiopia: evidence from EDHS 2016–2019 by Jenberu Mekurianew Kelkay, Deje Sendek Anteneh, Henok Dessie Wubneh, Abraham Dessie Gessesse, Gebeyehu Fassil Gebeyehu, Kalkidan Kassahun Aweke, Mikiyas Birhanu Ejigu, Mathias Amare Sendeku, Kirubel Adrissie Barkneh, Hasset Girma Demissie, Wubshet D. Negash, Birku Getie Mihret

“…An ensemble Machin learning algorithm using different classification models were implemented. …”
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