Exploring CycleGAN Technique for Improved Plant Disease Detection and Analysis by Ouyang Luyi

“…This paper tackles the problem by using Cycle-Consistent General Adversarial Networks (CycleGAN) to create artificial images of diseased plant leaves. …”
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ZZ-YOLOv11: A Lightweight Vehicle Detection Model Based on Improved YOLOv11 by Zhe Zhang, Zhongyang Zhang, Gang Li, Chenxi Xia

“…Aiming at the problems of insufficient vehicle detection accuracy, high misdetection and omission rate, and heavy model computational burden caused by complex lighting conditions, target occlusion, and other factors in urban traffic scenarios, this paper proposes an improved lightweight detection network, ZZ-YOLO. …”
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A Tale of Side Friction Elements in Dhaka City: From Modeling Real Cases to Revealing Impacts Through Event-Based Simulation by Ahmed Mahir Sultan Rumi, Hasan Nahiyan Nobel, A. H. M. Osama Haque, Abu Humayed Azim Fahmid, Tarik Reza Toha, Nouf Alaloula, Najla Abdulrahman Al-Nabhan, Abdulaziz Abdulrahman S. Alnamlah, A. B. M. Alim Al Islam

“…Moreover, while non-motorized traffic reduces the network’s average speed, it plays a crucial role in maintaining a good flow rate on Dhaka’s low-capacity roads.…”
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Combined Prediction Method of Short-Term Distance Headway Based on EB-GRA-TCN by Chun Wang, Weihua Zhang, Cong Wu, Heng Hu, Wenjia Zhu

“…Moreover, few studies have considered the time correlation between the historical DHW and the target DHW. To solve the above problems, a DHW prediction model is proposed in this paper by integrating entropy-based grey relation analysis (EB-GRA) and temporal convolutional network (TCN), named as EB-GRA-TCN model. …”
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Implementing a new clinical service – what’s your elevator pitch? by Ashvene Sureshkumar, Jillian Scandiffio, Dorothy Luong, Sarah Munce, Nanette Lai, Gregory Feng, Mark Bayley, Jiwon Oh, Monika Kastner, Andrea D. Furlan, Abhimanyu Sud, Anthony Feinstein, Robert Simpson

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Research on real-time monitoring method of mine personnel protective equipment with improved YOLOv8 by Lei ZHANG, Zhipeng SUN, Hongjing TAO, Shangkai HAO, Qianru YAN, Xiwei LI

“…BiFPN also introduces a weight that can be learned. Helps the network learn the importance of different input features. …”
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Multi-user joint task offloading and resource allocation based on mobile edge computing in mining scenarios by Siqi Li, Weidong Li, Wanbo Zheng, Yunni Xia, Kunyin Guo, Qinglan Peng, Xu Li, Jiaxin Ren

“…By introducing weighted coefficients for latency and energy consumption, the proposed method ensures that task completion latency does not exceed a predefined threshold while minimizing the overall system cost. The problem is formulated as a multi-objective optimization problem, which is solved using a two-layer alternating optimization framework. …”
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A Multidisciplinary and Longitudinal Framework for Enhancing Innovation Efficiency in Healthcare Systems by Szentpeteri JL, Szabo P, Liber N, Pandur E, Deak M, Csutak A, Sik A

“…Out of many identified problems, IT and process management stood out as a general problem in all eight analyzed clinics. …”
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A comparative analysis of variants of machine learning and time series models in predicting women’s participation in the labor force by Rasha Elstohy, Nevein Aneis, Eman Mounir Ali

“…Various machine learning (ML) algorithms, such as support vector machine (SVM), neural network, K-nearest neighbor (KNN), linear regression, random forest, and AdaBoost, in addition to popular time series algorithms, including autoregressive integrated moving average (ARIMA) and vector autoregressive (VAR) models, have been applied to an actual dataset from the public sector. …”
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Multi-Objective Parameter Optimization of Rotary Screen Coating Process for Structural Plates in Spacecraft by Yanhui Guo, Yanpeng Chen, Peibo Li, Xinfu Chi, Yize Sun

“…In order to solve the optimization problem, 108 sets of process experiments were designed, and then the experimental data were used to train a Back Propagation Neural Network (BPNN), a Least Squares Support Vector Machine (LSSVM), and Random Forest (RF) to obtain the best prediction model for the process parameters. …”
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Power Dispatch Stability Technology Based on Multi-Energy Complementary Alliances by Yiming Zhao, Chengjun Zhang, Changsheng Wan, Dong Du, Jing Huang, Weite Li

“…Particularly in handling intermittent power resources such as solar and wind energy, the proposed model effectively reduces peak shaving time and improves the overall network energy efficiency. Compared with the preference relationship based on selfish and Pareto sequence, the PGG-TS algorithm based on BMBT has an average utility of 10.2% and 25.3% in terms of load, respectively. …”
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Global Ionospheric TEC Forecasting for Geomagnetic Storm Time Using a Deep Learning‐Based Multi‐Model Ensemble Method by Xiaodong Ren, Pengxin Yang, Dengkui Mei, Hang Liu, Guozhen Xu, Yue Dong

“…Owing to the ionosphere's intricate and dramatic changes during geomagnetic storms, the high‐reliable prediction of the storm‐time ionospheric TEC remains a challenging problem. In this study, we developed a new deep learning‐based multi‐model ensemble method (DLMEM) to forecast geomagnetic storm‐time ionospheric TEC that combines the Random Forest (RF) model, the Extreme Gradient Boosting (XGBoost) algorithm, and the Gated Recurrent Unit (GRU) network with the attention mechanism. …”
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Research on CTSA-DeepLabV3+ Urban Green Space Classification Model Based on GF-2 Images by Ruotong Li, Jian Zhao, Yanguo Fan

“…The experimental results showed that the overall classification accuracy of the CTSA-DeepLabV3+ model is 96.21%, and the average intersection ratio, precision, recall, and F1-score reach 89.22%, 92.56%, 90.12%, and 91.23%, respectively, which is better than DeepLabV3+, Fully Convolutional Networks (FCNs), U-Net (UNet), the Pyramid Scene Parseing Network (PSPNet), UperNet-Swin Transformer, and other mainstream models. …”
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Low-Illumination Parking Scenario Detection Based on Image Adaptive Enhancement by Xixi Xu, Meiqi Zhang, Hao Tang, Weiye Xu, Bowen Sun, Zhu’an Zheng

“…Aiming at the problem of easily missed and misdetected parking spaces and obstacles in the automatic parking perception task under low-illumination conditions, this paper proposes a low-illumination parking space and obstacle detection algorithm based on image adaptive enhancement. …”
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A Data-Driven Method for Deriving the Dynamic Characteristics of Marginal Carbon Emissions for Power Systems by Bing Fang, Jiayi Zhang, Shuangyin Chen, Li Li, Shanli Wang, Mingzhe Wen

“…However, the existing research has normally considered the average carbon emissions as the indicator for the operation and planning of power systems. …”
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Enhancing Few-Shot SAR Ship Recognition: Pseudospectrum Information Generation and Fusion by Gui Gao, WenXi Liu, Xi Zhang

“…In order to solve the above problems, first, a SpecGenGANwith generating pseudospectrum information is proposed to solve the problem of missing spectrum information. …”
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Performance Analysis of Optical Wireless Channel Based on Beamforming Techniques Using Advanced Modulation Schemes by Lwaa Faisal Abdulameer, Adil Fadhil Mushatet, Tania Tariq Salim

“… The need for a very high data rate in the next-generation wireless network is growing, and optical wireless communication has become one of the best options for addressing this important problem. …”
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An urban road traffic flow prediction method based on multi-information fusion by Xiao Wu, Hua Huang, Tong Zhou, Yudan Tian, Shisen Wang, Jingting Wang

“…Spatio-Temporal Graph Neural Networks (STGNN) solves the problem of combining temporal properties and spatial dependence, but does not extract long-term trends and cyclical features of historical data. …”
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Increasing the uptake of cervical screening at cornerstone medical practice by Jessica Roberts, Joanna Bircher, Adeola Oyegbite

“…Background Nationally, cervical screening uptake is suboptimal, even though research shows that the programme is highly effective at preventing cervical cancer.Local problem Cornerstone is a small practice located in Salford in the North West of England. …”
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Hyperspectral Target Detection Based on Macro–Micro Spectrum Contrastive Learning by Jiacheng Tian, Dunbin Shen, Wenfeng Kong, Min Li, Hongyu Wang, Xiaorui Ma

“…Second, to distinguishing target knowledge, a multihead task-driven network is designed to learn discriminative features by integrating target spectrum into the band-wise correlation calculation. …”
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