Research on Side Lobe Suppression of Time-Modulated Sparse Linear Array Based on Particle Swarm Optimization by Lei Liang, Jie Sun, Hailin Li, Jialing Liu, Yachao Jiang, Jianjiang Zhou

“…An efficient pattern synthesis approach is proposed for the synthesis of a time-modulated sparse linear array (TMSLA) in this paper. …”
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A New Optimization Approach for Maximizing the Photovoltaic Panel Power Based on Genetic Algorithm and Lagrange Multiplier Algorithm by Mahdi M. M. El-Arini, Ahmed M. Othman, Ahmed Fathy

“…The technique which is based on objective function represents the output power of the PV panel and constraints, equality and inequality. …”
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A Three-Block Inexact Heterogeneous Alternating Direction Method of Multipliers for Elliptic PDE-Constrained Optimization Problems with a Control Gradient Penalty Term by Xiaotong Chen, Tongtong Wang, Xiaoliang Song

“…In some practical applications, it is necessary to smooth the control variables and suppress their large fluctuations, especially at the boundary. …”
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Feasibility and psychometric quality of smartphone administered cognitive ecological momentary assessments in women with metastatic breast cancer by Ashley M Henneghan, Emily W Paolillo, Kathleen M Van Dyk, Oscar Y Franco-Rocha, Soyeong Bang, Rebecca Tasker, Tara Kaufmann, Darren Haywood, Nicolas H Hart, Raeanne C Moore

“…Test-retest reliability was examined using intraclass correlation coefficients (ICCs) for each EMA, and Pearson's correlation were used to evaluate convergent validity between cognitive EMAs and baseline clinical cognitive and psychosocial variables. …”
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Optimization of Aerodynamic Design of a Winged UAV Through Genetic Algorithms and Large Eddy Simulation by Mohammad Javad Ebrahimi, Mahmoud Pasandidehfard, Ali Esmaeili, Mohammad Hossein Moghimi Esfandabadi

“…Optimization was conducted for six variables in a single stage, with 25 tests performed. …”
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Assessing the Effectiveness of DL-Clustering for Energy Optimization in Wireless Sensor Networks by Shailaja S. Halli, Poornima G Patil

“…Determining the fitness function allows us to estimate the player's stability over these variables. …”
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Optimal tuning of multi-PID controller using improved CMOCSO algorithm by Ying Hu, Xiongyan Liu, Hao Chen

“…In this model, the parameters are designated as decision variables, the performance index serves as the objective function, and the stability constraints of the system are incorporated. …”
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Performance Investigation of Coated Carbide Tools in Milling Procedures by Paschalis Charalampous

“…The optimization of the manufacturing conditions in milling processes composes a crucial task for enhancing machining efficiency and extending the tool’s lifespan. This study presents an investigation of the cutting tool’s performance under varying machining parameters via the generation of an experimental dataset that was obtained through laboratory-controlled milling operations. …”
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Decentralized queue control with delay shifting in edge-IoT using reinforcement learning by Viacheslav Kovtun

“…Analytical expressions for key QoS indicators (delay, variability, loss, energy consumption) as functions of the shift parameter are derived, and a multi-factor reward function is constructed. …”
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Understanding the Role of Organic Hole Transport Layers on Pinhole Blocking and Performance Improvement in Sb2Se3 Solar Cells by Thomas P. Shalvey, Christopher H. Don, Leon Bowen, Tim D. Veal, Jonathan D. Major

“…After successive record‐efficiencies using a range of device structures, spiro‐OMeTAD has emerged as the default hole transport material (HTM), however, the function of HTM layers remains poorly understood. …”
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Mi-DETR: For Mitosis Detection From Breast Histopathology Images an Improved DETR by Fatma Betul Kara Ardac, Pakize Erdogmus

“…In the decoder layer, unnecessary model parameters have been filtered out using a layer reduction strategy to improve model efficiency and reduce computational costs. Additionally, a more stable model has been obtained by using the CIoU loss function instead of the L1+GIoU loss function used in the DETR model. …”
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Solving 0-1 Knapsack and Bin Packing Problem Using Logical Social Group Optimization by Rhiddhi Prasad Das, Junali Jasmine Jena, Suresh Chandra Satapathy, Naeem M. S. Hannoon

“…This prominent research gap has been addressed in this paper by introducing Logical Social Group Optimization (LSGO), a logic-based binarized variant of Social Group Optimization (SGO) that leverages Boolean logic for improved efficiency. In LSGO, after the binarization by replacing the arithmetic operators with logical operators, one of the variables gets cancelled out. …”
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AESware: Developing AES-enabled low-power multicore processors leveraging open RISC-V cores with a shared lightweight AES accelerator by Eunjin Choi, Jina Park, Kyuseung Han, Woojoo Lee

“…AESware supports variable key lengths and ensures minimal power consumption with a compact design. …”
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Fuzzy rank fusion of deep neural networks for weed identification in groundnut crop by Akshay Dheeraj, Rajnish Kumar Chaturvedi, Sapna Nigam, Md. Ashraful Haque, Sudeep Marwaha

“…By combining selective and variable rate spraying, the smart herbicide sprayer effectively manages herbicide amounts. …”
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On the Modular Design Application for the Gas Turbine Sector: A Performance Optimization Approach in the Context of Industry 4.0 by Lucas Chavanel-Precloux, Roland Maranzana, Lucas A. Hof

“…Indeed, this study presents the functioning of the novel application, the different deployed components and their variables, such as the compressor efficiency, heat exchangers, or turbine stages, and the decision variable, e.g., the costs of generated energy. …”
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Research and Design of an Active Light Source System for UAVs Based on Light Intensity Matching Model by Rui Ming, Tao Wu, Zhiyan Zhou, Haibo Luo, Shahbaz Gul Hassan

“…Extensive qualitative and quantitative experiments confirm that the UAV active light source system based on light intensity matching proposed in this paper effectively enhances the effectiveness and robustness of vision-based tracking for multi-UAVs, particularly in complex and variable environments. This research provides an efficient and computationally effective solution for vision-based multi-UAV systems, further enhancing the visual tracking capabilities of multi-UAVs under complex conditions.…”
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Evaluating Machine Learning Models for Predicting Hardness of AlCoCrCuFeNi High-Entropy Alloys by Uma Maheshwera Reddy Paturi, Muhammad Ishtiaq, Pasupuleti Lakshmi Narayana, Anoop Kumar Maurya, Seong-Woo Choi, Nagireddy Gari Subba Reddy

“…This study evaluates the predictive capabilities of various machine learning (ML) algorithms for estimating the hardness of AlCoCrCuFeNi high-entropy alloys (HEAs) based on their compositional variables. Among the ML methods explored, a backpropagation neural network (BPNN) model with a sigmoid activation function exhibited superior predictive accuracy compared to other algorithms. …”
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Ionospheric Correction Based on Ingestion of Global Ionospheric Maps into the NeQuick 2 Model by Xiao Yu, Chengli She, Weimin Zhen, Nava Bruno, Dun Liu, Xinan Yue, Ming Ou, Jisheng Xu

“…The accuracy of TEC prediction can be improved further through performing a four-coefficient function expression of Az versus MODIP. …”
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Torsional Vibration Suppression During Mode Transition Process in a Parallel Hybrid Electric Vehicle Based on Multiple Model Predictive Control by Cheng Huang, Changqing Du, Longjian Li, Xiangyu Gongye, Yifan Zhao

“…At the same time, the influence of the cost function, the weight coefficient, and the predictive time domain on the torsional vibration suppression effect during the mode transition process are explored in the mMPC strategy design, and the solution time is controlled within 10ms, which meet the real-time requirements. …”
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Improving Electrical Distance Accuracy for Cable Fault Location Based on the Prony Method by Xiang Ren, Zhiqiang Feng, Kai Zhou, Xueming Zhou, Jianjun Yuan, Yefei Xu, Li Zhang

“…By establishing a frequency-variable coupling model containing the transfer function of the cable with double joint structure, studying the mapping relationship between the cable attenuation constant and the electromagnetic wave velocity, and adopting the Prony estimation method combined with the singular value decomposition noise reduction algorithm to achieve the extraction of the attenuation constant and the decoupling of the segmented wave velocity, thus improving the electrical accuracy of fault location. …”
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