Random forest model based fine scale spatiotemporal O₃ trends in the Beijing-Tianjin-Hebei region in China, 2010 to 2017

Ambient ozone (O₃) concentrations have shown an upward trend in China and its health hazards have also been recognized in recent years. High-resolution exposure data based on statistical models are needed. Our study aimed to build high-performance random forest (RF) models based on training data from 2013 to 2017 in the Beijing-Tianjin-Hebei (BTH) region in China at a 0.01 ° × 0.01 ° resolution, and estimated daily maximum 8h average O₃ (O₃-8hmax) concentration, daily average O₃ (O₃-mean) concentration, and daily maximum 1h O3 (O3-1hmax) concentration from 2010 to 2017. Model features included meteorological variables, chemical transport model output variables, geographic variables, and population data. The test-R² of sample-based O₃-8hmax, O₃-mean and O₃-1hmax models were all greater than 0.80, while the R² of site-based and date-based model were 0.68–0.87. From 2010 to 2017, O₃-8hmax, O₃-mean, and O₃-1hmax concentrations in the BTH region increased by 4.18 μg/m³, 0.11 μg/m³, and 4.71 μg/m³, especially in more developed regions. Due to the influence of weather conditions, which showed high contribution to the model, the long-term spatial distribution of O₃ concentrations indicated a similar pattern as altitude, where high concentration levels were distributed in regions with higher altitude

Modeling the Adaptation of Agricultural Production to Climate Change

Climate change and its impacts on agricultural production and food security are a significant source of public concern around the world [...

Метод розпізнавання DDos-атак на основі штучного інтелекту

Distributed Denial of Service (DDoS) has always been a key research object in the field of network security, which seriously threatens the development of network security in daily work and has a huge impact on the network environment. DDoS attack refers to the use of client/server technology to unite multiple computers as an attack platform to launch DDoS attacks against one or more targets, thereby multiplying the power of denial-of-service attacks. When a network device suffers a DDoS attack, the most obvious phenomenon is that the network device receives a large number of unknown packets and data streams. For enterprises, a company's network egress usually corresponds to a single IP, if there is an abnormal host in the enterprise, it may affect other users, so the enterprise security gateway needs to suppress and warn of abnormal behavior. However, the business traffic within an enterprise is very diverse, and it is difficult to accurately and effectively filter abnormal traffic, and it is impossible to distinguish normal sudden traffic. The current traffic inspection method is mainly based on deep packet inspection (D e e p Packet Inspection, DPI), which can only determine the type of traffic, and has limitations in the analysis of the specific behavior of the client, so it cannot effectively determine whether the network equipment of the enterprise has suffered a DDoS attack.Метою цієї статті є побудова простору ознак, що базується на основі кодів поведінки хоста та кодів функцій, щоб представити агреговані групи, пов’язані з операційними факторами та факторами поведінки програмного забезпечення в мережевому середовищі. Оскільки поведінка хоста та характеристики пакетів є хаотичною системою, що визначається багатьма факторами, для відстеження ненормальної поведінки в цій статті використовується побудова фазового простору для аналізу розміру області змін як вектора ознак часової області, щоб точніше визначити чи є поведінка хоста ненормальною в усіх варіантах простору ознак. Таким чином даний метод дозволяє краще й точніше попереджати про DDos-атаки

Optimal Irrigation under the Constraint of Water Resources for Winter Wheat in the North China Plain

The North China Plain (NCP) has the largest groundwater depletion in the world, and it is also the major production area of winter wheat in China. For sustainable food production and sustainable use of irrigated groundwater, it is necessary to optimize the irrigation amount for winter wheat in the NCP. Previous studies on the optimal irrigation amount have less consideration of the groundwater constraint, which may result in the theoretical amount of optimal-irrigation exceeding the amount of regional irrigation availability. Based on the meteorological data, soil data, crop variety data, and field management data from field experimental stations of Tangshan, Huanghua, Luancheng, Huimin, Nangong, Ganyu, Shangqiu, Zhumadian and Shouxian, we simulated the variation of yield and water use efficiency (WUE) under different irrigation levels by using the CERES-Wheat model, and investigated the optimal irrigation amount for high yield (OIy), water saving (OIWUE), and the trade-off between high yield and water saving (OIt) of winter wheat in the NCP. Based on the water balance theory, we then calculated the irrigation availability, which was taken as the constraint to explore the optimal irrigation amount for winter wheat in the NCP. The results indicated that the OIy ranged from 80 mm to 240 mm, and the OIWUE was 17% to 67% less than OIy, ranging from 0 mm to 200 mm. The OIt was between 80 mm and 240 mm, realizing the co-benefits of high yield and water saving. Finally, we determined the optimal irrigation amount (62–240 mm) by the constraint of irrigation availability. Our results can provide a realistic and scientific reference for the security of both grain production and groundwater use in the NCP

An Accurate and Efficient Quaternion-Based Visualization Approach to 2D/3D Vector Data for the Mobile Augmented Reality Map

Increasingly complex vector map applications and growing multi-source spatial data pose a serious challenge to the accuracy and efficiency of vector map visualization. It is true especially for real-time and dynamic scene visualization in mobile augmented reality, with the dramatic development of spatial data sensing and the emergence of AR-GIS. Such issues can be decomposed into three issues: accurate pose representation, fast and precise topological relationships computation and high-performance acceleration methods. To solve these issues, a novel quaternion-based real-time vector map visualization approach is proposed in this paper. It focuses on precise position and orientation representation, accurate and efficient spatial relationships calculation and acceleration parallel rendering in mobile AR. First, a quaternion-based pose processing method for multi-source spatial data is developed. Then, the complex processing of spatial relationships is mapped into simple and efficient quaternion-based operations. With these mapping methods, spatial relationship operations with large computational volumes can be converted into efficient quaternion calculations, and then the results are returned to respond to the interaction. Finally, an asynchronous rendering acceleration mechanism is also presented in this paper. Experiments demonstrated that the method proposed in this paper can significantly improve vector visualization of the AR map. The new approach, when compared to conventional visualization methods, provides more stable and accurate rendering results, especially when the AR map has strenuous movements and high frequency variations. The smoothness of the user interaction experience is also significantly improved

Estimations of forest water retention across China from an observation site-scale to a national-scale

202