A hybrid ensemble learning method for tourist route recommendations based on geo-tagged social networks

Geo-tagged travel photos on social networks often contain location data such as points of interest (POIs), and also users’ travel preferences. In this paper, we propose a hybrid ensemble learning method, BAyes-Knn, that predicts personalized tourist routes for travelers by mining their geographical preferences from these location-tagged data. Our method trains two types of base classifiers to jointly predict the next travel destination: (1) The K-nearest neighbor (KNN) classifier quantifies users’ location history, weather condition, temperature and seasonality and uses a feature-weighted distance model to predict a user’s personalized interests in an unvisited location. (2) A Bayes classifier introduces a smooth kernel function to estimate a-priori probabilities of features and then combines these probabilities to predict a user’s latent interests in a location. All the outcomes from these subclassifiers are merged into one final prediction result by using the Borda count voting method. We evaluated our method on geo-tagged Flickr photos and Beijing weather data collected from 1 January 2005 to 1 July 2016. The results demonstrated that our ensemble approach outperformed 12 other baseline models. In addition, the results showed that our framework has better prediction accuracy than do context-aware significant travel-sequence-patterns recommendations and frequent travel-sequence patterns.     

贵州后寨河喀斯特小流域水化学特征

通过分析后寨河流域内各测站的水化学资料,讨论了流域内各点的水化学类型及其空间分布,分析了水化学类型的形成原因,并详细讨论了水量的季节变化和人为因素对水中离子含量变化的影响。      

An artificial neural network model for flood simulation using GIS: Johor River Basin, Malaysia

Flooding is one of the most destructive natural hazards that cause damage to both life and property every year, and therefore the development of flood model to determine inundation area in watersheds is important for decision makers. In recent years, data mining approaches such as artificial neural network (ANN) techniques are being increasingly used for flood modeling. Previously, this ANN method was frequently used for hydrological and flood modeling by taking rainfall as input and runoff data as output, usually without taking into consideration of other flood causative factors. The specific objective of this study is to develop a flood model using various flood causative factors using ANN techniques and geographic information system (GIS) to modeling and simulate flood-prone areas in the southern part of Peninsular Malaysia. The ANN model for this study was developed in MATLAB using seven flood causative factors. Relevant thematic layers (including rainfall, slope, elevation, flow accumulation, soil, land use, and geology) are generated using GIS, remote sensing data, and field surveys. In the context of objective weight assignments, the ANN is used to directly produce water levels and then the flood map is constructed in GIS. To measure the performance of the model, four criteria performances, including a coefficient of determination (R ²), the sum squared error, the mean square error, and the root mean square error are used. The verification results showed satisfactory agreement between the predicted and the real hydrological records. The results of this study could be used to help local and national government plan for the future and develop appropriate (to the local environmental conditions) new infrastructure to protect the lives and property of the people of Johor.     

白垩纪中期海相富有机碳沉积的地球生物学背景

白垩纪中期(约125～88Ma)海相富有机碳沉积广泛发育于全球各主要洋盆和沉降区,是许多大油田的重要烃源岩。文中从地球生物学的角度探讨了当时海相富有机碳沉积的地质背景和主控因素,认为在白垩纪中期全球事件频发的特殊背景下,保存条件(大洋缺氧)和生产力的提高共同控制了有机质的富集。大洋缺氧不但加快了海洋生物的灭绝和更替,使有机质大量堆积,而且促进了营养元素(P、N、Fe等)的再生和厌氧自养型海洋微生物(如蓝细菌、绿硫细菌和古菌类等)的极度繁盛,提高了生产力水平;而高的生产力又反过来加剧了海洋的缺氧。新的研究成果(Os同位素证据)表明,白垩纪大规模海底火山作用引发了持续的温室效应和海水循环的静滞、紊乱以及弱上升流发育,进而导致生产力的提高和大洋缺氧事件(OAE)的发生,最终造成有机质的广泛堆积和保存。     

Comparison Between GAMIL, and CAM2 on Interannual Variability Simulation

Recently, a new atmospheric general circulation model （GAMIL： Grid-point Atmospheric Model of IAP LASG） has been developed at the Institute of Atmospheric Physics （IAP）, Chinese Academy of Sciences （CAS）, which is based on the Community Atmospheric Model Version 2 （CAM2） of the National Center for Atmospheric Research （NCAR）. Since the two models have the same physical processes but different dynamical cores, the interannual variability simulation performances of the two models are compared. The ensemble approach is used to reduce model internal variability. In general, the simulation performances of the two models are similar. Both models have good per- formance in simulating total space-time variability and the Southern Oscillation Index. GAMIL performs better in the Eastern Asian winter circulation simulation than CAM2, and the model internal variability of GAMIL has a better response to external forcing than that of CAM2. These indicate that the improvement of the dynamic core is very important. It is also verified that there is less predictability in the middle and high latitudes than in the low latitudes.     

青藏高原东边缘冕宁—宜宾剖面电性结构及高导层的地质意义

约50Ma前印度板块与欧亚板块开始碰撞之后,青藏高原发生了令人瞩目的整体隆升,成为晚第三纪以来亚洲乃至全球最为重要的地质事件,并使青藏高原成为大陆岩石圈变形最为强烈的地区之一,是全球学者研究大陆动力学乃至地球动力学的焦点和热点地区。由于印度板块与欧亚板块的碰撞以及组成青藏高原各地块向东和东南的挤出运动,位于青藏高原东边缘大凉山地块及其附近地区具有明显的高原和盆地之间的过渡带特征,地壳变形严重,地壳厚度变化剧烈,并且是重力梯度带和航磁异常明显的地区,也是（GPS）资料显示的地壳运动方向由东向东南发生转变的关键地段。本区不仅蕴藏有丰富的金属矿等矿产资源,也是我国强烈地震最为频繁的地区之一。     

Dynamic assessment and early warning of ecological security: a case study of the Yangtze river urban agglomeration

Natural Hazards - Ecological security is vital to the survival of human beings and critical to the sustainable development of socioeconomic environment. In view of the deficiencies of the static...     

中国沿海围网技术参数的分析和比较

本文对中国沿海几十种围网的技术参数进行了分析和比较。     

Petrogenesis of potassic alkaline volcanics associated with rapakivi granites in the Proterozoic rift of Beijing,China

Summay A suite of potassic alkaline volcanites is spatially and temporally associated with rapakivi granites which are related to Proterozoic (1.85 to 1.40 Ga) rifting in the Beijing area. The volcanites are spread along an EW-trending 150 km long sea basin rift and the rapakivi granites were emplaced along a major EW-fault in nn adjacent uplifted region. The alkaline magmatism is comparable to the middle Proterozoic anorogenic magmatism in North America and Fennoscandia and is related to incipient breakup of the craton they intrude. The volcanic rocks and the rapakivi granites show within plate affinities. They also have similar overall REE distribution patterns that are enriched in LREE. The rapakivi granites show larger negative Eu anomalies than the volcanites. The data suggest that the rapakivi granites were crystallised from a more evolved magma than the volcanic rocks.

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Petrogenese von K-reichen, alkalischen Vulkaniten in Assoziation mit Rapakivi-Graniten im proterozoischen Peking-Rift, China

Zusammenfassung Eine Serie von K-reichen, alkalischen Vulkaniten ist räumlich und zeitlich mit Rapakivi-Graniten, die mit dem proterozoischen (1.85 bis 1.40 Mia) Rifting in der Peking Region im Zusammenhang stehen, assoziiert. Die Vulkanite treten entlang eines E-W-streichenden, 150 km langen Riftbeckens auf, die Rapakivi-Granite kommen entlang einer EW Hauptstörung in einer angrenzenden Hebungszone vor. Der Alkali-Magmatismus ist mit dem mittelproterozoischen, anorogenen Magmatismus in Nordamerika und Fennoskandien vergleichbar und mit einem beginnenden Aufbrechen des Kratons ver bunden. Sowohl die Vulkanite, wie auch die Rapakivi-Granite zeigen Intraplatten-Affinität. Sie zeigen generell ähnliche SEE Verteilungsmuster, die an LSEE angereichert sind. Die Rapakivi-Granite zeigen weiters eine stärkere, negative Eu-Anomalie als die Vulkanite. Diese Daten weisen darauf hin, daß die Rapakivi-Granite aus einem höher entwickelten Magma als die Vulkanite entstanden sind.

     

A novel CFAR tonal detector using phase compensation

A novel tonal detector is presented in this paper. The detector uses phase compensation for detecting sinusoidal signal with unknown amplitude, frequency, and phase in complex Gaussian noise with unknown variance. We analyze the statistical properties of the discrete Fourier transform (DFT) of the observations and consider the leakage effect. Then we develop the detector by using generalized likelihood ratio test (GLRT). The new detector fully utilizes the phase information of the signal and achieves constant false alarm rate (CFAR) property. Theoretical analysis and simulation results show its improvement in detection performance.