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.…”
Get full text

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.…”
Get full text

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. …”
Get full text

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

Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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. …”
Get full text

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

Get full text

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). …”
Get full text

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. …”
Get full text

Robust Adaptive Path Tracking Control Scheme for Safe Autonomous Driving via Predicted Interval Algorithm by Cong Phat Vo, Jungeun Lee, Jeong Hwan Jeon

Get full text

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. …”
Get full text

Machine Learning Innovations for Improving Mineral Recovery and Processing: A Comprehensive Review* by Korie, Josephmartin Izuchukwu*, Chudi-Ajabor, Ogochukwu Gabriela, Ezeonyema, Chukwudalu Chukwuekezie, Oshim, Francisca Ogechukwu

Get full text

Selective opposition based constrained barnacle mating optimization: Theory and applications by Marzia Ahmed, Mohd Herwan Sulaiman, Md. Maruf Hassan, Md. Atikur Rahaman, Masuk Abdullah

“…In addition to increasing efficiency by cutting down on wasted time spent exploring, this also increases the likelihood of stumbling onto optimal solutions. After that, it is put through its paces in a real-world case study, where it proves to be superior to the most cutting-edge algorithms available.…”
Get full text

Structural optimization and performance evaluation of a sugarcane leaf mulching machine by Weihua Huang, Shuo Wang, Chang Ge, Lijiao Wei, Dongjie Du, Zhaojun Niu, Ming Li, Zhenhui Zheng

“…Field tests under typical post-harvest conditions (leaf moisture content of 31.8 %, representing the average humidity of sugarcane leaves in tropical regions) demonstrated that the optimized machine achieved a pick-up rate of 98.4 % and a mulching rate of 94.4 % (≤20 cm), reflecting improvements of 0.8 % and 7.1 % over the previous design, respectively. …”
Get full text

Entire aerial-aquatic trajectory modeling and optimization for trans-medium vehicles by Teng Long, Nianhui Ye, Baoshou Zhang, Jingliang Sun, Renhe Shi

“…Simultaneously, several constraints, i.e., the max impact load, trajectory height, etc., are involved in the optimization problem. Rather than directly optimizing by a heuristic algorithm, a multi-surrogate cooperative sampling-based optimization method is proposed to alleviate the computational complexity of the entire trajectory optimization problem. …”
Get full text

RIS-assisted terahertz frequency band vehicle network capacity optimization by Fatang CHEN, Xiaoling LIU, Dan WANG, Ruofan ZHANG

“…In order to alleviate the spectrum scarcity and capacity limitation of the current wireless system, the terahertz frequency band was introduced and the reconfigurable intelligent surface (RIS) was used for auxiliary communication to construct a downlink vehicle network.Considering the constraints of limited total system power, QoS constraints of cellular mobile users, and randomness constraints of vehicle and user locations, a hybrid optimization model was established for optimal power allocation and optimal deployment of RIS with the aim of maximizing the total rate of vehicle users.Based on the balance method, linear transformation method, and element elimination method, the original NP-hard problem was transformed into a convex optimization problem with complex correlation constraints and multivariate coupling.The inner layer iteration was based on the Lagrange multiplier method to solve the optimal power allocation, and the outer layer iteratively solved the optimal deployment of RIS based on a improved genetic algorithm.The simulation results show that rationally deploying the number and distribution density of RIS nodes based on optimal power allocation can save costs while achieving a higher target total capacity.…”
Get full text