Integrated deep learning for cardiovascular risk assessment and diagnosis: An evolutionary mating algorithm-enhanced CNN-LSTM by Ahmed Mohammed Ahmed Alsarori, Mohd Herwan Sulaiman

“…EMA was applied for hyperparameter optimization, demonstrating improved convergence and generalization over conventional methods. …”
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Optimization of Toolpath Planning and CNC Machine Performance in Time-Efficient Machining by Arbnor Pajaziti, Orlat Tafilaj, Afrim Gjelaj, Besart Berisha

“…We propose a method that integrates advanced algorithms to identify and eliminate redundant movements, optimize the toolpaths, and improve the machining strategies. …”
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Resource allocation strategy based on optimal matching auction in the enterprise network by Xin CONG, Lingling ZI, Xueli SHEN

“…To address the issue that the owners of computer are selfish in the enterprise networks,which caused the low available number of resource nodes and low efficiency of resource allocation,an optimized matching resource allocation strategy OMRA was proposed and its core was the auction mechanism.Selfishness was restrained and the number of available resources was increased by OMRA,so as the operating efficiency of the whole auction market was improved.First,the initial prices were determined by normalizing the costs of different type of resources on the beginning of auction.Secondly,an optimal matching auction algorithm was designed to maximize the interests of the auction markets.Then,service perfecting algorithm was performed such that the sellers could get more services at the current transaction value,thus ensuring the benefits of resource providers.At last,a request price updating algorithm was adopted to assurance that both sellers and buyers could get priorities in the next auction processing.Compared with the cloud resource allocating algorithm via fitness-enabled auction (CRAA/FA),the experiment results indicate that the efficiency of resource allocation improves by 10% and the benefits of market increase by 11.4%.…”
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Solution Approach to the Minimum Spanning Tree Problem in Tsukamoto Fuzzy and Fermantean Fuzzy Environments by Desli de Haas, Citra Palembang, Aziz Rumakefing

“…Solving Fuzzy Minimum Spanning Tree (FFMST) and Fuzzy Tsukamoto using modified Prim Algorithm for Undirected Graphs and modified Optimal Branching Algorithm for Directed Graphs in FFN environment. …”
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Dynamic Coal Flow-Based Energy Consumption Optimization of Scraper Conveyor by Qi Lu, Yonghao Chen, Xiangang Cao, Tao Xie, Qinghua Mao, Jiewu Leng

“…Conversely, simultaneously increasing both chain and drum speeds helps to maintain lump coal size. The final optimization scheme demonstrates this balance—achieving improved energy efficiency at the cost of increased coal fragmentation. …”
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MODEL FOR THE FORMATION OF A PROJECT TEAM COMPOSITION BASED ON DISCRETE OPTIMIZATION METHODS by S.M. Beketov, M.V. Dergachev, S.G. Redko

“…The problem lies in the need to improve the efficiency and effectiveness of projects by optimizing the composition of teams. …”

Optimization mechanism of attack and defense strategy in honeypot game with evidence for deception by Lihua SONG, Yangyang JIANG, Changyou XING, Guomin ZHANG

“…Using game theory to optimize honeypot behavior is an important method in improving defender’s trapping ability.Existing work tends to use over simplified action spaces and consider isolated game stages.A game model named HoneyED with expanded action spaces and covering comprehensively the whole interaction process between a honeypot and its adversary was proposed.The model was focused on the change in the attacker’s beliefs about its opponent’s real identity.A pure-strategy-equilibrium involving belief was established for the model by theoretical analysis.Then, based on the idea of deep counterfactual regret minimization (Deep-CFR), an optimization algorithm was designed to find an approximate hybrid-strategy-equilibrium.Agents for both sides following hybrid strategies from the approximate equilibrium were obtained.Theoretical and experimental results show that the attacker should quit the game when its belief reaches a certain threshold for maximizing its payoff.But the defender’s strategy is able to maximize the honeypot’s profit by reducing the attacker’s belief to extend its stay as long as possible and by selecting the most suitable response to attackers with different deception recognition abilities.…”
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Optimization of Identification and Zoning Method for Landscape Characters of Urban Historic Districts by Hong YUN, Zixuan HU, Zehao HU

“…Then the research utilizes K-means clustering algorithm to optimize the zoning method for historic landscape characters. …”
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Optimized detection of insertions/deletions (INDELs) in whole-exome sequencing data. by Bo-Young Kim, Jung Hoon Park, Hye-Yeong Jo, Soo Kyung Koo, Mi-Hyun Park

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Optimization of microwave components using machine learning and rapid sensitivity analysis by Slawomir Koziel, Anna Pietrenko-Dabrowska

“…On the other hand, the most widely used nature-inspired algorithms require large numbers of system simulations to yield a satisfactory design. …”
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Shape optimization of non-uniform parametric piezoelectric energy harvester beam by Milad Hasani, Hossein Shahverdi

“…The model, validated through finite element method (FEM) simulations and experimental data, enables rapid analysis and optimization of PEHs. The Nelder-Mead optimization algorithm was employed to enhance power generation performance across three cross-sectional configurations: rectangular, trapezoidal, and quadratic. …”
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Multi-Attribute Collaborative Optimization for Multimodal Transportation Based on User Preferences by Youpeng Lu, Gang Gao

“…In terms of solution methods, an improved Genetic Algorithm (GA) and Aptenodytes Forsteri Optimization (AFO) hybrid algorithm (GA-AFO) is proposed, which introduces GA to generate a high-quality initial population to accelerate convergence. …”
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Research on pose estimation algorithm of non-cooperative target tracked vehicles based on PnP model by Zhigang Ren, Xinagjun Tang, Guoquan Ren, Dinghai Wu

“…Finally, the pose equation is solved by finding the local minimum of the cost function through algebraic optimization, thus avoiding convergence issues in iterative optimization. …”
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Binary program taint analysis optimization method based on function summary by Pan YANG, Fei KANG, Hui SHU, Yuyao HUANG, Xiaoshao LYU

“…Taint analysis is a popular software analysis method, which has been widely used in the field of information security.Most of the existing binary program dynamic taint analysis frameworks use instruction-level instrumentation analysis methods, which usually generate huge performance overhead and reduce the program execution efficiency by several times or even dozens of times.This limits taint analysis technology’s wide usage in complex malicious samples and commercial software analysis.An optimization method of taint analysis based on function summary was proposed, to improve the efficiency of taint analysis, reduce the performance loss caused by instruction-level instrumentation analysis, and make taint analysis to be more widely used in software analysis.The taint analysis method based on function summary used function taint propagation rules instead of instruction taint propagation rules to reduce the number of data stream propagation analysis and effectively improve the efficiency of taint analysis.For function summary, the definition of function summary was proposed.And the summary generation algorithms of different function structures were studied.Inside the function, a path-sensitive analysis method was designed for acyclic structures.For cyclic structures, a finite iteration method was designed.Moreover, the two analysis methods were combined to solve the function summary generation of mixed structure functions.Based on this research, a general taint analysis framework called FSTaint was designed and implemented, consisting of a function summary generation module, a data flow recording module, and a taint analysis module.The efficiency of FSTaint was evaluated in the analysis of real APT malicious samples, where the taint analysis efficiency of FSTaint was found to be 7.75 times that of libdft, and the analysis efficiency was higher.In terms of accuracy, FSTaint has more accurate and complete propagation rules than libdft.…”
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Efficient and Composable Masked AES S-Box Designs Using Optimized Inverters by Vedad Hadžic, Roderick Bloem

“… Hardware implementations of cryptographic algorithms are susceptible to power analysis attacks, allowing attackers to break the otherwise strong security guarantees. …”
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Classification of finger movements through optimal EEG channel and feature selection by Murside Degirmenci, Yilmaz Kemal Yuce, Matjaž Perc, Matjaž Perc, Matjaž Perc, Matjaž Perc, Matjaž Perc, Yalcin Isler

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Greedy gradient-free adaptive variational quantum algorithms on a noisy intermediate scale quantum computer by César Feniou, Muhammad Hassan, Baptiste Claudon, Axel Courtat, Olivier Adjoua, Yvon Maday, Jean-Philip Piquemal

“…However, practical implementations on current quantum processing units (QPUs) are challenging due to the noisy evaluation of a polynomially scaling number of observables, undertaken for operator selection and high-dimensional cost function optimization. We introduce an adaptive algorithm using analytic, gradient-free optimization, called Greedy Gradient-free Adaptive VQE (GGA-VQE). …”
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Enhancing LoRaWAN Performance Using Boosting Machine Learning Algorithms Under Environmental Variations by Maram A. Alkhayyal, Almetwally M. Mostafa

“…Bayesian Optimization was applied to fine-tune hyperparameters to improve model accuracy. …”
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Robust Adaptive Path Tracking Control Scheme for Safe Autonomous Driving via Predicted Interval Algorithm by Cong Phat Vo, Jungeun Lee, Jeong Hwan Jeon

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Optimization of Flight Scheduling in Urban Air Mobility Considering Spatiotemporal Uncertainties by Lingzhong Meng, Minggong Wu, Xiangxi Wen, Zhichong Zhou, Qingguo Tian

“…Additionally, the proposed phased artificial lemming algorithm (ALA) outperforms traditional optimization algorithms in terms of solution quality. …”
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