A high performance approach to ensure image security during transmission by Adithya S Nair, Charvi Upreti, Advaith Arun, Renuka Devi S

“…The randomization is achieved through a Mersenne Twister algorithm. This project uses parallelization techniques to optimize computational performance and reduce the runtime. …”
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Consider the master-slave game model of integrated energy system with step carbon trading and demand response by Yi Zhang, Zhezhou Zhang

“…In the context of deepening energy coupling and the high penetration of renewable energy, this paper proposes a master-slave game model incorporating comprehensive demand response and a stepped carbon trading mechanism. The goal is to optimize scheduling of demand response resources and fully leverage the flexibility of energy use within an integrated energy system while addressing conflicts of interest among multiple stakeholders, thereby enhancing trading revenue in Energy Markets while considering lower carbon emissions. …”
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Real-Time Series Arc Fault Detection and Appliances Classification in AC Networks Based on Competing Convolutional Kernels by Francesco Ferracuti, Riccardo Felicetti, Luca Cavanini, Patrick Schweitzer, Andrea Monteriu

“…To reduce inference time and optimize the algorithm for embedded control units, a feature reduction strategy is employed. …”
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Research on productivity prediction method of infilling well based on improved LSTM neural network: A case study of the middle-deep shale gas in South Sichuan by GUAN Wenjie, PENG Xiaolong, ZHU Suyang, YANG Chen, PENG Zhen, MA Xiaoran

“…In order to quickly and accurately predict the production capacity of infilling wells, this study classifies the “three-stage” declining trend observed in the production pressure curves of existing wells into: (1) A drastic decline period, regarded as the initial water production stage; (2) a rapid decline period; and (3) a slow decline period, both considered part of the later gas production stage. The Grey Wolf Optimizer(GWO) algorithm, a fast optimization algorithm with adaptive capabilities and an information feedback mechanism, is applied for hyperparameter optimization of the Long Short-term Memory (LSTM) neural network. …”
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Efficient tuna detection and counting with improved YOLOv8 and ByteTrack in pelagic fisheries by Yuanchen Cheng, Zichen Zhang, Yuqing Liu, Jie Li, Zhou Fu

“…This paper proposes an automatic tuna counting method based on the YOLOv8n-DMTNet target detection algorithm combined with the improved ByteTrack tracking algorithm. …”
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Temporal Community Detection and Analysis with Network Embeddings by Limengzi Yuan, Xuanming Zhang, Yuxian Ke, Zhexuan Lu, Xiaoming Li, Changzheng Liu

“…To address these issues, we propose TCDA-NE, a novel TCD algorithm that combines evolutionary clustering with convex non-negative matrix factorization (Convex-NMF). …”
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ARIMA-Kriging and GWO-BiLSTM Multi-Model Coupling in Greenhouse Temperature Prediction by Wei Zhou, Shuo Liu, Junxian Guo, Na Liu, Zhenglin Li, Chang Xie

“…This study introduces an ARIMA-Kriging spatiotemporal coupling model, which combines temperature time-series data with sensor spatial coordinates to accurately determine minimum temperatures in greenhouses while reducing hardware costs. Utilizing the high-quality data processed by this model, this study proposes and constructs a novel Grey Wolf Optimizer and Bidirectional Long Short-Term Memory (GWO-BiLSTM) temperature prediction framework, which combines a Grey Wolf Optimizer (GWO)-enhanced algorithm with a Bidirectional Long Short-Term Memory (BiLSTM) network. …”
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An Effective Heuristic-Based Approach for Partitioning by Xibin Zhao, Hehua Zhang, Yu Jiang, Songzheng Song, Xun Jiao, Ming Gu

“…We note that the genetic algorithm has a strong global search capability, while the simulated annealing algorithm will fail in a local optimal solution easily. …”
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Research on High-Reliability Energy-Aware Scheduling Strategy for Heterogeneous Distributed Systems by Ziyu Chen, Jing Wu, Lin Cheng, Tao Tao

“…Second, to address the time-varying reliability characteristics introduced by DVFS, we propose a Fibonacci search-based dynamic frequency scaling algorithm (SEFFA). This algorithm effectively reduces energy consumption while ensuring task reliability, achieving sub-optimal processor energy adjustment. …”
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Intelligent Energy Management in an Isolated DC Microgrid using Fuzzy Logic by Youssfi Abdelaziz, El Kadi Youssef Ait

“…The PV system is controlled by a MPPT method implementing the INC algorithm, while the storage system is managed by a PI controller to control battery charging and discharging. …”
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Hybrid precoding and power allocation for mmWave NOMA systems based on time delay line arrays by Gangcan SUN, Xinli WU, Wanming HAO, Zhengyu ZHU

“…Specifically,the Dinkelbach method is applied in the outer layer to transform the fractional structure of the objective function in EE optimization into a subtractive structure, and the non-convex objective function is transformed into a convex function by using mathematical tools in the inner layer, and then an iterative algorithm based on alternating optimization (AO) is proposed for power allocation, and finally the solution of the initial problem is obtained by circular iteration in both inner and outer layers. …”
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Adaptive Scheduling and Routing Scheme for Delay Guarantee in Wireless Sensor Networks by Yan Sun, Cong Chen, Hong Luo

“…Motivated by this, we propose an adaptive scheduling and routing scheme for guaranteeing dynamic end-to-end delay requirement while minimizing the energy consumption. First of all, we utilize an optimal wake-up scheduling algorithm to achieve the initial wake-up schedules and routes and design an adaptive adjustment algorithm. …”
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SA3C-ID: a novel network intrusion detection model using feature selection and adversarial training by Wanwei Huang, Haobin Tian, Lei Wang, Sunan Wang, Kun Wang, Songze Li

“…Subsequently, the refined data undergoes feature selection employing an improved pigeon-inspired optimizer (PIO) algorithm. This operation eliminates redundant and irrelevant features, consequently reducing data dimensionality while maintaining critical information. …”
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Local Alignment of DNA Sequence Based on Deep Reinforcement Learning by Yong-Joon Song, Dong-Ho Cho

“…<italic>Goal:</italic> Over the decades, there have been improvements in the sequence alignment algorithm, with significant advances in various aspects such as complexity and accuracy. …”
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Big Data-Driven 3D Visualization Analysis System for Promoting Regional-Scale Digital Geological Exploration by Yiping Tian, Jiongqi Wu, Genshen Chen, Gang Liu, Xialin Zhang

“…Experimental validation shows the improved CMMN algorithm reduces cloud task completion time by 2.37% while increasing resource utilization by 0.652% compared with conventional methods. …”
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Energy-Efficient User Association Strategy for Hyperdense Heterogeneous Networking in the Fifth Generation Systems by Lei Li, Hao Jin, Zhipeng Yan, Changqing Yang, Yong Wu

“…We focus on the solution of the biconcave framework, and, by exploiting the biconcave structure, a novel iterative algorithm based on dual theory is proposed, where a partially optimal solution can be achieved. …”
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TCCM: Trajectory Converged Chaff-Based Mix-Zone Strategy for Enhancing Location Privacy in VANET by Yunheng Wu

“…Additionally, the TCCM strategy incorporates a genetic algorithm to optimize mix zone placement and ensure a balance between privacy protection and resource efficiency. …”
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Adaptive enhancement of shoulder x-ray images using tissue attenuation and type-II fuzzy sets. by Qifeng Liu, Yong Han, Lu Shen, Jialei Du, Marzia Hoque Tania

“…The method integrates automatic tissue attenuation techniques, which enhance the image contrast by removing non-essential tissue components while preserving important tissues and bones. Additionally, we apply an improved Type-II fuzzy set algorithm to further optimize image sharpness. …”
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LCDDN-YOLO: Lightweight Cotton Disease Detection in Natural Environment, Based on Improved YOLOv8 by Haoran Feng, Xiqu Chen, Zhaoyan Duan

“…A Focal-EIoU loss function is also integrated to optimize the model’s training process. Experimental results show that compared to YOLOv8, the LCDDN-YOLO model reduces the number of parameters by 12.9% and the floating-point operations (FLOPs) by 9.9%, while precision, mAP@50, and recall improve by 4.6%, 6.5%, and 7.8%, respectively, reaching 89.5%, 85.4%, and 80.2%. …”
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Protein structural domain-disease association prediction based on heterogeneous networks by Jingpu Zhang, Lianping Deng, Lei Deng

“…Small proteins are often found to be composed of only a single domain, while most large proteins consist of multiple domains for achieving various composite cellular functions. …”
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