Improved RT-DETR Framework for Railway Obstacle Detection by Peng Li, Yanhui Peng, Su-Mei Wang, Cheng Zhong

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Flight Connection Planning for Low-Cost Carriers Under Passenger Demand Uncertainty by Wenhao Ding, Max Z. Li, Eri Itoh

“…The model determines the optimal set of connecting itineraries to introduce over the existing network of flights, identifies promising transfer airports, and provides passenger allocation strategies across flights. …”
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Attention-Based Multi-Objective Control for Morphing Aircraft by Qien Fu, Changyin Sun

“…Subsequently, an auxiliary problem, employing <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>ϵ</mi></semantics></math></inline-formula>-constraint and augmented state methods, is introduced to yield a finite and locally Lipschitz continuous value function, which facilitates the construction of a neural network controller. Furthermore, a multi-phase pseudospectral method is derived to discretize the auxiliary problem and formulate the corresponding nonlinear programming problem, where open loop optimal solutions of the multi-task flight mission are generated. …”
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A data-driven approach for predicting remaining intra-surgical time and enhancing operating room efficiency by Saleem Ramadan, Mohammad Abu-Shams, Sameer Al-Dahidi, Ibrahim Odeh, Najat Almasarwah

“…Purpose: Efficient scheduling in Operating Rooms (ORs) is essential for optimizing corresponding costs and enhancing customer satisfaction in healthcare systems. …”
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MGL-YOLO: A Lightweight Barcode Target Detection Algorithm by Yuanhao Qu, Fengshou Zhang

“…Moreover, it also demonstrates advantages in average precision compared to other object detection networks, proving the effectiveness of MGL-YOLO for one-dimensional barcode detection in complex backgrounds.…”
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Transfer learning based EfficientNet method for transmission line insulator flaw detection by Aleena Swetapadma, Anamika Yadav

“…EfficientNetB3 may be chosen as the optimal network owing to its high accuracy and less complex structure. …”
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DKA-YOLO: Enhanced Small Object Detection via Dilation Kernel Aggregation Convolution Modules by Yicheng Qiu, Feng Sha, Li Niu

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Triple-E Principle: Leveraging Occam&#x2019;s Razor for Dance Energy Expenditure Estimation by Kuan Tao, Kun Meng, Bingcan Gao, Junchao Yang, Junqiang Qiu

“…A bidirectional stepwise regression model incorporating heart rate or triaxial motion sequences from accelerometers achieved an average goodness-of-fit of 0.73, identifying optimal accelerometer sites based on Efficiency principle. …”
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A Combined Frame Difference and Convolution Method for Moving Vehicle Detection in Satellite Videos by Xin Luo, Jiatian Li, Xiaohui A, Yuxi Deng

“…Next, the initial features are processed by a backbone network to further extract spatiotemporal feature information. …”
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A High-Performance and Lightweight Maritime Target Detection Algorithm by Shidan Sun, Zhiping Xu, Xiaochun Cao, Jiachun Zheng, Jiawen Yang, Ni Jin

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Modification, Simulation and Demonstration of Laboratory Scale Pelton Turbine for Waterfall Hydropower Plant by Lawal Muhammed Nasir, Oluwatoyin Lanre Seriki, Emmanuel Onche

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A novel hybrid extreme learning machine-based diagnosis model for sensor node faults in aquaculture by Bing Shi, Zelin Gao, Tianheng Pu, Jianming Jiang, Yueping Sun

“…The inertia weight $$\omega$$ and learning factor c were optimized to enhance the optimization ability of the particle swarm. …”
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Daily-Scale Fire Risk Assessment for Eastern Mongolian Grasslands by Integrating Multi-Source Remote Sensing and Machine Learning by Risu Na, Byambakhuu Gantumur, Wala Du, Sainbuyan Bayarsaikhan, Yu Shan, Qier Mu, Yuhai Bao, Nyamaa Tegshjargal, Battsengel Vandansambuu

“…Utilizing fire point data from eastern Mongolia (2012–2022), we fused multiple feature variables and developed and optimized three models: random forest (RF), XGBoost, and deep neural network (DNN). …”
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Prediction of Blast Vibration Velocity of Buried Steel Pipe Based on PSO-LSSVM Model by Hongyu Zhang, Shengwu Tu, Senlin Nie, Weihua Ming

“…These were compared with BP neural network model and Sa’s empirical formula. The results show that the fitting correlation coefficient (R2), root mean square error (RMSE), average relative error (MRE), and Nash coefficient (NSE) of the PSO-LSSVM model for the prediction of pipeline peak vibration velocity are 91.51%, 2.95%, 8.69%, and 99.03%, showing that the PSO-LSSVM model has a higher prediction accuracy and better generalization ability, which provides a new idea for the vibration velocity prediction of buried pipelines under complex blasting conditions.…”
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Residential Energy Management Method Based on the Proposed A3C-FER by Jinjiang Zhang, Qiang Lin, Lu Wang, Orefo Victor Arinze, Zihan Hu, Yantai Huang

“…In comparison with the Proximal Policy Optimization (PPO) and Deep Q-Network (DQN) algorithms, the novel approach not only improves the average reward value post-convergence by 38.48% and 47.17%, respectively, but also significantly reduces the training duration by 81.19% within a multi-threaded computational environment.…”
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3D animation design image detail enhancement based on intelligent fuzzy algorithm by Pu Haitao, Pu Yuang

“…The image was divided into superpixel regions using SLIC (Simple Linear Iterative Clustering) algorithm, and local features such as texture, contrast, and edge intensity were extracted; in the SRGAN model, the generator improved image resolution through deep residual blocks and Convolutional Neural Network (CNN), while the discriminator optimized the generated image quality through adversarial training; at the same time, a Fuzzy Logic System (FLS) was constructed to dynamically adjust the image fuzzy degree; channel and spatial attention modules in the generator were integrated to enhance key area details. …”
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Study on the gas outflow pattern and outflow prediction model of the return mining face under complex geological conditions by Yi Sun, Lulin Zheng, Hong Lan, Zhaoxing Yu, Jin Wang, Bo Li, Feng Yang, Fangbo Wen

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DGSS-YOLOv8s: A Real-Time Model for Small and Complex Object Detection in Autonomous Vehicles by Siqiang Cheng, Lingshan Chen, Kun Yang

“…The key innovation lies in the synergistic integration of several architectural enhancements: the DCNv3_LKA_C2f module, leveraging Deformable Convolution v3 (DCNv3) and Large Kernel Attention (LKA) for better the capture of complex object shapes; an Optimized Feature Pyramid Network structure (Optimized-GFPN) for improved multi-scale feature fusion; the Detect_SA module, incorporating spatial Self-Attention (SA) at the detection head for broader context awareness; and an Inner-Shape Intersection over Union (IoU) loss function to improve bounding box regression accuracy. …”
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A hybrid ARIMA-BP approach for superior accuracy in predicting traffic accident losses by Jian Liu, Zhuqing Zhang, Bin Lyu, Rui Feng, Ye He

“…In this study, these challenges are addressed by integrating the autoregressive integrated moving average (ARIMA) model with the backpropagation (BP) neural network model. …”
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Time-Series Interval Forecasting with Dual-Output Monte Carlo Dropout: A Case Study on Durian Exports by Unyamanee Kummaraka, Patchanok Srisuradetchai

“…Deep neural networks (DNNs) are prominent in predictive analytics for accurately forecasting target variables. …”
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