Student dropout is a serious problem globally. It affects not only the individual who drops out but also former school, family, and society in general. With current development of science technology, big data emphasized as most significant technology analysis. From recorded educational data, efficient prediction students' currently hot topic research. Previous studies have focused on based specific levels such individual, middle university level. However, ensemble learning approaches...

Expressway section speed can visually reflect the operation condition, and accurate short time prediction has a wide range of applications in path planning traffic guidance. However, existing expressway data have defects, such as sparse density incomplete object challenges. Thus, this paper proposes framework for combined model based on wavelet transform spatial-temporal graph convolutional network (WSTGCN) Electronic Toll Collection (ETC) gantry transaction data. First, pre-processes ETC to...

This study proposes a novel log end face feature extraction and matching method based on Swin Transformer V2, aiming to address limitations in accuracy speed faced by traditional deep learning models, like InceptionResNetV2 Vision Transformer. Accurate identification is crucial for forestry wood supply chain management, especially given the growing reliance timber imports meet industrial demands construction, furniture manufacturing, paper production. Our dataset comprises images of...

Autonomous vehicles are increasingly becoming a part of our daily lives, with active chassis control systems playing pivotal role and drawing significant attention from both academia industry. Current research on vehicle-to-vehicle overtaking behavior predominantly focuses low-to-moderate speeds, insufficient studies addressing high-speed lane-changing maneuvers. Under conditions, the variability complexity road environments significantly increase tracking errors, posing challenges for...

A microarray can be easily used for quantitatively analyzing the expression levels of DNA genes. Yet, noises introduced during application will greatly affect accuracy sequence detection. How to reduce noise constitutes a challenging problem in analysis. Especially, due weak fluorescence response, image contains difficulties low peak-signal-to-noise ratio (PSNR) and luminance contrast. To solve that wavelet threshold denoising method has poor effective on PSNR image, approach based...

Abstract Marine Predator Algorithm (MPA) is an optimization algorithm inspired by the behavior of predator and prey to catch their own food. MPA simple easy implement. To further improve performance MPA, this paper proposes a Multigroup (MGMPA). The multigroup mechanism divide initial population into several independent groups. These groups generate top Elite matrix based on different strategies share information after fixed iteration. Above include maximum same group, average verify its...

As one of the largest Internet Things systems in world, China’s expressway electronic toll collection (ETC) generates nearly billion pieces transaction data every day, recording traffic trajectories almost all vehicles on expressway, which has great potential application value. However, there are inevitable missed transactions and false ETC system, leads to certain missing rates data. In this work, a dynamic search step SegrDTW algorithm based an improved DTW is proposed according...

Abstract With the rapid development of economy, sharp increase in number urban cars and backwardness road construction lead to serious traffic congestion roads. Many scholars have tried their best solve this problem by predicting congestion. Some traditional models such as linear nonlinear been proved a good prediction effect. However, with increasing complexity network, these can no longer meet higher demand without considering more complex comprehensive factors, spatio-temporal correlation...

With the acceleration of urbanization and increasing demand for travel, current road traffic is experiencing rapid growth more complex spatio-temporal logic. Vehicle tracking on roads presents several challenges, including scenes with frequent foreground–background transitions, fast nonlinear vehicle movements, presence numerous unavoidable low-score detection boxes. In this paper, we propose AM-Vehicle-Track, following proven-effective paradigm by (TBD). At stage, introduce lightweight...

Object detection in autonomous driving scenarios has become a popular task recent years. Due to the high-speed movement of vehicles and complex changes surrounding environment, objects different scales need be detected, which places high demands on performance network model. Additionally, devices have varying capabilities, lightweight model is needed ensure stable operation with limited computing power. To address these challenges, we propose called BiGA-YOLO based YOLOv5. We design...

Object detection in images taken by unmanned aerial vehicles (UAVs) is drawing ever-increasing research interests. Due to the flexibility of UAVs, their shooting altitude often changes rapidly, which results drastic scale size identified objects. Meanwhile, there are many small objects obscured from each other high-altitude photography, and background captured also complex variable. These problems lead a colossal challenge with object UAV photography images. Inspired characteristics eagles,...

Abstract Management of connected vehicles at unsignalised intersections is a large‐scale complex problem with safety constraints and time‐varying unsolved variables, which crucial but hard to solve online. A faster coordination system, however, not only benefits from smaller time granularity find optimum, also has more robustness towards scenario fast‐moving vehicle nodes. This paper proposes real‐time scheme consisting three stages. (a) Target velocity optimisation: collision‐free passage...

The travel time prediction of vehicles is an important part intelligent expressways. It can not only provide the vehicle distribution trend each section for expressway management department to assist fine expressway, but it also owners with dynamic and accurate services formulate more reasonable plans. However, there are still some problems in current research (e.g., different types processed separately, proximity road network considered, capture information spatial-temporal perspective...

As one of the great advances in modern technology, microarray is widely used many fields, including biomedical research, clinical diagnosis, and so on. Evidently, order to extract intensity fluorescence bio-probes accurately, we need pay special attention gridding at first. To solve poor effect traditional Otsu method for gridding, an innovative algorithm optimized by multilevel thresholds proposed improve accuracy effectiveness image segmentation. The experimental results indicate that...

Using deep reinforcement learning to solve traffic signal control problems is a research hotspot in the intelligent transportation field. Researchers have recently proposed various solutions based on methods for problems. However, most optimization takes maximization of capacity as goal, ignoring concerns pedestrians at intersections. To address this issue, we propose pedestrian-considered method. The method combines network and strategy with efficiency safety aspects. At same time, waiting...

Identifying traffic congestion accurately is crucial for improving the expressway service level. Because distributions of microscopic quantities are highly sensitive to slight changes, measurement affected by many factors. As an essential part expressway, areas should be considered when measuring state. Although existing studies pay increasing attention areas, impact caused hard measure evaluating events. By merging ETC transaction datasets and area entrance data, this work proposes a with...

Accident severity prediction is a hot topic of research aimed at ensuring road safety as well taking precautionary measures for anticipated future crashes. In the past decades, both classical statistical methods and machine learning algorithms have been used to predict traffic crash severity. However, most these models suffer from several drawbacks including low accuracy, lack interpretability people. To address issues, this paper proposed hybrid Balanced Bagging Classification (BBC) Light...

The rapid growth of online car hailing provides an excellent opportunity to provide convenient travel services. However, with the tremendous increase users and taxis, car-hailing prediction systems face several challenges: 1) difficulty modeling nonlinear spatiotemporal interactions between vehicles, 2) incorporating context information multimodal attribute enhancement data, 3) problems data sparsity. To cope these challenges, we propose a novel fusion graph convolutional network (MFGCN) for...

The spatio-temporal pattern recognition of time series data is critical to developing intelligent transportation systems. Traffic flow are that exhibit patterns periodicity and volatility. A novel robust Fourier Graph Convolution Network model proposed learn these effectively. includes a Embedding module stackable Spatial-Temporal ChebyNet layer. development the based on analysis theory can capture features. layer designed traffic flow’s volatility features for improving system’s robustness....

Abstract With the rapid development of expressway Electronic Toll Collection (ETC) technology in China, management system is becoming digital and intelligent, which provides a solid foundation for vehicle infrastructure cooperation autonomous driving. The gantry position key part ETC system. However, there are still some problems (e.g. missing or false), can seriously affect intelligent expressways. To address these two issues, an positioning method proposed. First, transaction data GPS on...