Building a model-based personalised recommendation approach for tourist attractions from geotagged social media data

When travelling, people are accustomed to taking and uploading photos on social media websites, which has led to the accumulation of huge numbers of geotagged photos. Combined with multisource information (e.g. weather, transportation, or textual information), these geotagged photos could help us in constructing user preference profiles at a high level of detail. Therefore, using these geotagged photos, we built a personalised recommendation system to provide attraction recommendations that match a user's preferences. Specifically, we retrieved a geotagged photo collection from the public API for Flickr (Flickr.com) and fetched a large amount of other contextual information to rebuild a user's travel history. We then created a model-based recommendation method with a two-stage architecture that consists of candidate generation (the matching process) and candidate ranking. In the matching process, we used a support vector machine model that was modified for multiclass classification to generate the candidate list. In addition, we used a gradient boosting regression tree to score each candidate and rerank the list. Finally, we evaluated our recommendation results with respect to accuracy and ranking ability. Compared with widely used memory-based methods, our proposed method performs significantly better in the cold-start situation and when mining ‘long-tail’ data.     

三疣梭子蟹肌肉乳化病的病原及其致病性研究

为进一步搞清养殖梭子蟹肌肉乳化病的病原及其致病机理,找到有效的防治方法,2002-2004年在浙江省宁波、舟山等地养殖场,从濒死的梭子蟹体内分离出1205-11和1205-21两株菌。通过菌体形态、培养特性和生理生化反应,鉴定这2株菌分别为溶藻弧菌(Vibrio alginolyticus)和葡萄牙假丝酵母(Candida lusitaniae)。人工感染试验证实,这2株菌是梭子蟹肌肉乳化病的病原菌,葡萄牙假丝酵母为继发性感染病原,蟹体外部的损伤及蟹之间相互残伤可能是传染的主要途径。     

植被高光谱特征分析及其病害信息提取研究

高光谱(hyperspectral)遥感是20世纪末地球观测系统中最重要的技术突破之一。根据植被高光谱数据的植被冠层光谱反射特征和诊断性光谱吸收特征,利用光谱连续统去除法,探讨光谱一阶微分反射比(FDR)和从连续统去除的光谱吸收特征中获得的波段深度(BD)、连续统去除后微分反射比(CRDR)、波段深度比(BDR)和归一化波段深度指数(NBDI)等光谱特征参量。结合多时相的条锈病小麦PHI航空高光谱影像,分析条锈病对小麦光谱的影响及其光谱特征,并运用光谱特征参量和波谱角制图(SAM)技术监测和识别小麦条锈病。     

A new approach for vegetation change detection in urban areas

IntroductionVegetation distribution and change is regardedas ani mportant sign of urban environment . Withcity expanding and population increasing, herecomes a series of problems on environment ,andmoreover ,greening ratio is regarded as a stand-ard of ci…     

Applications of conditional nonlinear optimal perturbation to the study of the stability and sensitivity of the Jovian atmosphere

A two-layer quasi-geostrophic model is used to study the stability and sensitivity of motions on smallscale vortices in Jupiter’s atmosphere. Conditional nonlinear optimal perturbations (CNOPs) and linear singular vectors (LSVs) are both obtained numerically and compared in this paper. The results show that CNOPs can capture the nonlinear characteristics of motions in small-scale vortices in Jupiter’s atmosphere and show great difference from LSVs under the condition that the initial constraint condition is large or the optimization time is not very short or both. Besides, in some basic states, local CNOPs are found. The pattern of LSV is more similar to local CNOP than global CNOP in some cases. The elementary application of the method of CNOP to the Jovian atmosphere helps us to explore the stability of variousscale motions of Jupiter’s atmosphere and to compare the stability of motions in Jupiter’s atmosphere and Earth’s atmosphere further.     

一种新的实时电磁逆散射方法

为解决介质圆柱体逆散射问题,提出一种新的在线逆散射方法,通过支持向量机将逆散射问题转化成一个回归估计问题. 该方法可应用于各种逆散射方面, 尤其是目标的几何与电磁参数重构和埋地目标探测. 文中首次将支持向量机方法应用到该领域,设置多个散射场的观测点,通过提取散射场的不同信息作为样本信息训练支持向量机, 建立了介质圆柱体的逆散射模型, 利用该模型重构了介质圆柱体的电磁参数,同时探测了埋地位置. 数值结果显示了该方法的有效性和准确性,为目标的实时逆散射研究提供了一种有效方法.     

华东地区态矢量的研究

态矢量来源于统计物理学,是对连续场进行粗粒化描述的方法。尹祥础等把该方法移植到地震学中用以定量刻画地震活动性的演化,取得较好的结果。作者对华东地区1970年以来发生5级以上12次地震进行了分析,总结震前态矢量的变化情况,发现震前态矢量均有显著变化,为本地区地震趋势预测提供一定的参考价值。     

基于SVR和LSTM算法反演散射计下有效波高研究

有效波高反演对于海洋工程及海洋环境安全具有重要意义.我国海洋二号(HY-2A)卫星载有散射计和高度计等获取海洋要素的仪器.散射计可获取海洋风场数据但无法直接获取有效波高数据,高度计可获取海洋有效波高数据但覆盖区域狭小.本文将散射计与高度计各自优势结合,利用支持向量回归(SVR)和长短期记忆(LSTM)智能算法反演散射计...     

The cooperative and conflictual interactions between the United States,Russia, and China: A quantitative analysis of event data

The United States, Russia and China are militarily and economically among the most powerful countries in the post-Cold War period, and the interactions between the three powers heavily influence the international system. However, different conclusions about this question are generally made by researchers through qualitative analysis, and it is necessary to objectively and quantitatively investigate their interactions. Monthly-aggregated event data from the Global Data on Events, Location and Tone(GDELT) to measure cooperative and conflictual interactions between the three powers, and the complementary cumulative distribution function(CCDF) and the vector autoregression(VAR) method are utilized to investigate their interactions in two periods: January, 1991 to September, 2001, and October, 2001 to December, 2016. The results of frequencies and strengths analysis showed that: the frequencies and strengths of USA-China interactions slightly exceeded those of USA-Russia interactions and became the dominant interactions in the second period. Although that cooperation prevailed in the three dyads in two periods, the conflictual interactions between the USA and Russia tended to be more intense in the second period, mainly related to the strategic contradiction between the USA and Russia, especially in Georgia, Ukraine and Syria. The results of CCDF indicated that similar probabilities in the cooperative behaviors between the three dyads, but the differences in the probabilities of conflictual behaviors in the USA-Russia dyad showed complicated characteristic, and those between Russia and China indicated that Russia had been consistently giving China a hard time in both periods when dealing with conflict. The USA was always an essential factor in affecting the interactions between Russia and China in both periods, but China's behavior only played a limited role in influencing the interactions between the USA-Russia dyad. Our study provides quantitative insight into the direct cooperative and conflictual interactions between the three dyads since the end of the Cold War and helps to understand their interactions better.     

空间分析与生物地球化学循环:西藏林周县大骨节病患病村与非患病村的比较研究

西藏林周县是我国大骨节病(KBD)患病较为严重的地区之一,本文将林周县作为研究区,通过使用地理探测器(GeoDetector)量化分析KBD患病率风险因子的影响,并使用环境化学方法验证空间分析结果。通过对10个潜在影响因子的分析以及对当地KBD患病村和非患病村的土壤-水-粮食-人这一生物地球化学循环的环境化学分析,结果表明:(1)林周县KBD由一组多重且交互作用的环境影响因子共同作用影响,其中最重要的控制因子是地层因子;(2)所有环境介质(土壤、水、谷物)及人体组织中的硒元素浓度在KBD患病区均低于非患病区;(3)当地居民对硒和铬的摄入严重不足,尤其是KBD患病村中居民硒元素平均日摄入量(ADD)大约仅为世界卫生组织(WHO)建议的成人基本摄入量下限的4%;(4)我们推测,当地居民患病主要是由于地层这一影响因子,这是由于通过生态系统的迁移转化导致当地人口严重硒缺乏,最终导致地方性生物地球化学硒缺乏。