Optimizing PAPR performance for 6G OTFS waveform using adaptive genetic PTS method for Rician fading channels by Arun Kumar, Aziz Nanthaamornphong, Nishant Gaur

“…Abstract This paper proposes a novel method for reducing the peak-to-average power ratio (PAPR) in orthogonal time–frequency space (OTFS) modulation over Rician fading channels using an adaptive genetic algorithm-based partial transmit sequence (AGA-PTS) technique. …”
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RESE-CNN: Residual Squeeze-and-Excitation Network for High-Contrast Optical Tomography Reconstruction by Zhu Yingkuang, Pan Zhenhua, Li Huajun, Chen Jianyang, Sheng Yihao

“…In this work, a sophisticated optical tomography (OT) system coupled with an innovative reconstruction algorithm is presented. The system architecture includes 25 light sources and 25 strategically placed fan-beam receivers. …”
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Adaptive Policy-Oriented Cybersecurity: A Decentralized Framework Using Message Passing Algorithms for Dynamic Threat Mitigation by Spyridon Evangelatos, Eleni Veroni, Mariza Konidi, Sophia Karagiorgou, Georgia Dede, Anargyros Baklezos, Christos Nikolopoulos, Panagiotis Sarigiannidis, Sotirios K. Goudos

“…More specifically, we extend the traditional Min-Sum algorithm by incorporating dynamic trust weights that influence policy enforcement decisions, allowing more reliable nodes to have a greater impact while mitigating the risks posed by untrusted entities. …”
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Scheduling optimization based on particle swarm optimization algorithm in emergency management of long-distance natural gas pipelines. by Huichao Guo, Runhua Huang, Shuqin Cheng

“…The experimental results show that compared with the traditional particle swarm optimization algorithm, NACFPSO performs well in both convergence speed and scheduling time, with an average convergence speed of 81.17 iterations and an average scheduling time of 200.00 minutes; while the average convergence speed of the particle swarm optimization algorithm is 82.17 iterations and an average scheduling time of 207.49 minutes. …”
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Fast DOA Estimation Based on the Transform Domain Weighted Noise Subspace Fitting Algorithm for Generalized Sparse Array by Chunxi Liu, Zhikun Chen, Dongliang Peng

“…At present, most DOA estimation algorithms are only suitable for the uniform arrays, while a few DOA estimate algorithms that can be applied to the GSA are unsatisfactory in terms of computational speed and accuracy. …”
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An Efficient Algorithm for Resource Allocation in Mobile Edge Computing Based on Convex Optimization and Karush–Kuhn–Tucker Method by Kaijing Wang, Shelily F. Akhtar, Fahad Ahmed Al-Zahrani

“…Simulation results show that the proposed algorithm has better computational offloading and resource allocation performance as compared to existing algorithms.…”
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AI-Based Prediction of Warpage in Organic Substrates by Jingyi Zhao, Meiying Su, Rui Ma

“…However, traditional experimental approaches incur high costs, while case-by-case finite element method (FEM) modeling presents computational bottlenecks. …”
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Fast and computationally efficient generative adversarial network algorithm for unmanned aerial vehicle–based network coverage optimization by Marek Ružička, Marcel Vološin, Juraj Gazda, Taras Maksymyuk, Longzhe Han, MisCha Dohler

“…To assess the performance of the proposed approach, we compare it with the optimal core-set algorithm and quasi-optimal spiral algorithm. Simulation results show that the proposed approach converges to the quasi-optimal solution with a negligible difference from the global optimum while maintaining a quadratic complexity regardless of the number of users.…”
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A node deployment algorithm for maximizing network lifetime in delay-constrained duty-cycled wireless sensor networks by Thi-Nga Dao, Seokhoon Yoon

“…In order to address the hot spot problem and long end-to-end delay, this article proposes a novel energy-balanced node deployment algorithm for maximizing network lifetime in duty-cycled wireless sensor networks while taking into account a delay requirement. …”
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De-noising algorithms for the raised cosine pulse signal using the minimum-energy frame in the discrete signal space by Ying-hai XIE, Wei YANG, Ting-ting FAN

“…The de-noising algorithms were proposed for the raised cosine pulse signal using minimum-energy(wavelet) frame in the discrete signal space.For the given two minimum-energy frames,the decomposition coefficients of sampled sequence appeared significant statistical characteristics difference between the raised cosine pulse signal and additive Gaussian noise under the frames’sub-sequences.Based on this,two threshold de-noising algorithms were provided to makes full use of the merit that the frame was fit for the de-noising work,they removed partial noise component while keeping the component of original signal and got effic nt de-noising result.The simulation results show that,when the modulating method is BPSK and its raised cosine pulse signal is polluted by the additive Gaussian noise,then if add a pre-processing link to denoise the receiving waveform using the algorithms,the receiver can greatly increase the signal-to-noise ratio of receiving signal and have about 3.1dB and 2.7dB performance gain of bit error ratio,respectively.…”
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Information Diffusion Interpolation Model Based on the PSO-CV Algorithm and Its Application on Source Regions of the Yellow River by HUANG Huaping, YIN Kaixia, JIN Gaoyang

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A Side Lobe Level Reduction Method Using Simulated Annealing Algorithm in a Uniform Arc Array by Song-Il KANG, Kyong-Sim U, Kyong-Chol CHOE, Yong-Kwang RI, Hyok-Il KYE

“…This paper presents a method to effectively reduce the side lobe level while minimizing the main lobe width increase. This is done using the simulated annealing algorithm (SAA) for a uniformly spaced arc array of omnidirectional underwater acoustic transducers, even at low signal-to-noise ratio (SNR). …”
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De-noising algorithms for the raised cosine pulse signal using the minimum-energy frame in the discrete signal space by Ying-hai XIE, Wei YANG, Ting-ting FAN

“…The de-noising algorithms were proposed for the raised cosine pulse signal using minimum-energy(wavelet) frame in the discrete signal space.For the given two minimum-energy frames,the decomposition coefficients of sampled sequence appeared significant statistical characteristics difference between the raised cosine pulse signal and additive Gaussian noise under the frames’sub-sequences.Based on this,two threshold de-noising algorithms were provided to makes full use of the merit that the frame was fit for the de-noising work,they removed partial noise component while keeping the component of original signal and got effic nt de-noising result.The simulation results show that,when the modulating method is BPSK and its raised cosine pulse signal is polluted by the additive Gaussian noise,then if add a pre-processing link to denoise the receiving waveform using the algorithms,the receiver can greatly increase the signal-to-noise ratio of receiving signal and have about 3.1dB and 2.7dB performance gain of bit error ratio,respectively.…”
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Enhanced Community Detection via Convolutional Neural Network: A Modified Approach Based on MRFasGCN Algorithm by Puneet Kumar, Dalwinder Singh, Mamoona Humayun, Ali Alqazzaz, Arun Malik, Ibrahim Alrashdi, Isha Batra, Ghadah Naif Alwakid

“…After Experiments NMI value for MRFasGCN on DBLP data set is 0.662 while for Modified MRFasGCN it is 0.672, Modified MRFasGCN algorithm provides significant improvement of 2.9% in performance as compared to MRFasGCN. …”
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Optimization of Nitrogen Fertilization Strategies for Drip Irrigation of Cotton in Large Fields by DSSAT Combined with a Genetic Algorithm by Zhuo Yu, Weiguo Fu

“…Field validations across contrasting growing seasons demonstrate the framework’s capacity to reduce nitrogen inputs by 15–20% while increasing profitability by 8–12% compared to conventional practices, without compromising yield stability. …”
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A Monte Carlo Tree Search-Based Load Balancing Algorithm for 6G Indoor Heterogeneous Networks by Guanghui Ma, Syifaul Fuada, Marcos Katz

“…By dynamically predicting future network states, the proposed algorithm optimally distributes traffic, improving overall network performance. …”
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Influence of Genetic Algorithm Parameters on Their Performance for Parameter Identification of a Yeast Fed-batch Fermentation Process Model by Maria Angelova, Tania Pencheva

“…Almost all applied SGA and MGA led to similar values of the optimization criterion but the SGA with operators’ sequence mutation, crossover and selection, and MGA with operators’ sequence crossover, selection and mutation, are significantly faster than others while keeping the model accuracy. Among the considered GA parameters, generation gap influences most significantly to SGA and MGA convergence time, saving of about 40% of computational time of the algorithms without affecting the model accuracy.…”
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Public Sentiment Analysis on the Boycott Israel Movement on Platform X Using Random Forest and Logistic Regression Algorithms by Rachmayanti Tri Agustin, Yana Cahyana, Kiki Ahmad Baihaqi, Tatang Rohana

“…The Random Forest model achieved an accuracy of 70%, while Logistic Regression reached 68%. Both models showed higher accuracy in predicting positive sentiment compared to negative and neutral. …”
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New jitter-aware network coding approach for packet selection in wireless mesh network using Jacobsen algorithm by Rasoul Nikoee Saravani, Seyed Javad Mirabedini

“…Related computations are performed through Jacobson algorithm. According to simulation results, selecting a proper coding pattern for jitter can improve jitter by 30% while the throughput of this method shows no considerable change compared with that of available methods.…”
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Enhanced Robust Control of Induction Motor Using Combined Optimal Model Predictive Control With Super-Twisting Algorithm by REZGUI, S.-E., NEMOUCHI, B.

“…This paper presents a novel strategy for induction motor control that combines Optimal Model Predictive Control (OMPC) with the Super-Twisting Algorithm (STA) to enhance the performance of field-oriented control (IFOC) strategy under disturbances and uncertainties. …”
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