四川盆地龙门山北段隐伏构造带特征及其油气勘探意义

2014年以来,四川盆地西北部(以下简称川西北)龙门山山前带双鱼石地区上古生界天然气勘探获得重大发现,先后在中二叠统栖霞组、中泥盆统观雾山组钻获多口工业气井。随着勘探工作的稳步推进,深入开展龙门山逆冲推覆构造前锋带—山前带构造特征研究,是认识该区上古生界气藏特征、拓展油气勘探领域的重要前提。为此,基于新部署的线束三维地震、重磁电资料以及ST9等井的实钻成果,解剖了龙门山逆冲推覆构造前锋带—山前带的构造特征,进而分析了该区隐伏构造带的构造特征、天然气成藏条件和勘探前景。结果表明:(1)龙门山逆冲推覆构造前锋带(1)号隐伏断裂之下发育大型隐伏构造带,其地层受挤压褶皱变形,发育下三叠统嘉陵江组以下的海相地层;(2)由南到北(1)号断裂底部滑脱层位由浅变深,从南部的寒武系滑脱,向北部逐渐转换为基底卷入,古生界及其以上地层整体抬升,越向北抬升幅度越大,断裂上下盘之间的位移距离、褶皱幅度也越大,北部相对南部上古生界构造整体抬升约1 500 m;(3)在剑阁以西—广元地区,(1)号断裂东侧整体表现出"三级台阶"的构造格局。结论认为:龙门山逆冲推覆构造前锋带(1)号断裂下盘隐伏构造带面积达1 800 km2,具有优越的天然气成藏条件,其中观雾山组和栖霞组储集条件、保存条件好,是川西北深层海相层系天然气勘探拓展寻找新突破的重要领域,具有现实的油气勘探意义。     

Recognition of occupational therapy exercises and detection of compensation mistakes for Cerebral Palsy

Depth camera-based virtual rehabilitation systems are gaining attention in occupational therapy for cerebral palsy patients. When developing such a system, domain-specific exercise recognition is vital. To design such a gesture recognition method, some obstacles need to be overcome: detection of gestures not related to the defined exercise set and recognition of incorrect exercises performed by the patients to compensate for their lack of ability. We propose a framework based on hidden Markov models for the recognition of upper extremity functional exercises. We determine critical compensation mistakes together with restrictions for classifying these mistakes with the help of occupational therapists. We first eliminate undefined gestures by evaluating two models that produce adaptive threshold values. Then we utilize specific negative models based on feature thresholding and train them for each exercise to detect compensation mistakes. We perform various tests using our method in a laboratory environment under the supervision of occupational therapists.     

SINA: Semantic interpretation of user queries for question answering on interlinked data

The architectural choices underlying Linked Data have led to a compendium of data sources which contain both duplicated and fragmented information on a large number of domains. One way to enable non-experts users to access this data compendium is to provide keyword search frameworks that can capitalize on the inherent characteristics of Linked Data. Developing such systems is challenging for three main reasons. First, resources across different datasets or even within the same dataset can be homonyms. Second, different datasets employ heterogeneous schemas and each one may only contain a part of the answer for a certain user query. Finally, constructing a federated formal query from keywords across different datasets requires exploiting links between the different datasets on both the schema and instance levels. We present Sina, a scalable keyword search system that can answer user queries by transforming user-supplied keywords or natural-languages queries into conjunctive SPARQL queries over a set of interlinked data sources. Sina uses a hidden Markov model to determine the most suitable resources for a user-supplied query from different datasets. Moreover, our framework is able to construct federated queries by using the disambiguated resources and leveraging the link structure underlying the datasets to query. We evaluate Sina over three different datasets. We can answer 25 queries from the QALD-1 correctly. Moreover, we perform as well as the best question answering system from the QALD-3 competition by answering 32 questions correctly while also being able to answer queries on distributed sources. We study the runtime of SINA in its mono-core and parallel implementations and draw preliminary conclusions on the scalability of keyword search on Linked Data.     

浅论企业潜亏的成因及防范策略

论述了会计信息是经过加工或者处理后的会计数据，是从填制原始凭证到形成财务报表结束的处理过程。管理者对会计信息的操纵，其目的就是通过改变财务报表所反映的状况和经营业绩来影响管理者的决策，以满足企业利益最大化。要防止企业潜亏，就必须了解形成潜亏的形式及成因，采取相应的对策，保证企业和国家利益不受损失，杜绝潜亏的产生和漫延。     

混合井箕斗与罐笼同时运行摩擦问题处理

针对弓长岭中央深井区混合井箕斗与罐笼在同时运行时相互摩擦，存在严重的安全隐患致使混合井一直不能正常运行的问题，通过现场实际测量和理论计算对比分析，提出有针对性的具体措施，实现了混合井箕斗与罐笼同时安全运行。     

文君小区套内无梁无柱住宅结构设计

哈尔滨市文君小区 8号楼为套内无梁无柱小高层住宅。介绍了通过合理布置与板同厚的预应力混凝土暗梁将异形板规则化处理的方法 ;给出了楼盖配筋预应力筋的配筋图 ,为设计同类工程提供了参考     

城市发展中的潜在危机

发展可以提升城市生活品质，但它不全是正向的，常常伴随许多负面效应，这些负面效应被城市发展成就掩盖的同时，正在威胁着我们的安全。城市快速发展伴随着城市安全隐患产生，虽然这些隐患常常被忽视，但是它们聚集起来时，就成为城市潜在的危机。城市防灾除了减少自然灾害的破坏外，防范8大安全隐患应是其重要的组成部分。     

基于HMM的无线充电系统PFC装置故障检测

PFC装置作为电动汽车无线充电系统中整流模块与高频逆变模块之间的重要桥梁,一旦发生故障,不仅会对电网产生严重的影响,还会对后端高频逆变模块造成不可逆的破坏,因此需要对其进行快速和准确的故障检测。传统故障检测方法检测时间长,检测精度低。为此,本文提出一种基于隐马尔可夫模型（Hidden Markov Model,HMM）的电动汽车无线充电系统PFC装置故障检测方法。首先初始化模型,然后利用鲍姆韦尔奇（Baum-Welch）算法进行故障模型训练,最后利用维特比（Viterbi）算法进行故障检测。仿真实验结果表明,采用HMM进行PFC装置故障检测的正确率较神经网络和支持向量机（Support Vector Machine,SVM）最大提高了约40%,是一种快速且准确的方法,因此本文采用HMM能够有效识别出电动汽车无线充电系统中PFC装置故障的类型。     

Weldability of low-alloy steels in submersion-arc welding at high linear energies

Results of analysis of investigations of welded joints produced in welding low-alloy high-strength 07G2NDMFBT steel at linear energies up to 6 kJ/mm show that the proposed combinations of welding materials and the technology of multi-arc submerged-arc welding result in high hot-cracking resistance and high properties of the weld metal. However, regardless of the high cold-cracking resistance of the steel, in welding at high heat inputs there is a considerable degradation of the structure and the toughness of the metal in the coarse-grained region of the heat-affected zone decreases under the effect of the welding thermal cycle. Consequently, it is concluded that the weldability of this steel is limited and it is therefore necessary to apply restrictions in the practical application of the processes with high heat input.     

An on-line SAX and HMM-based anomaly detection and visualization tool for early disturbance discovery in a dynamic industrial process

In order to achieve an optimum and successful operation of an industrial process, it is important firstly to detect upsets, equipment malfunctions or other abnormal events as early as possible and secondly to identify and remove the cause of those events. Univariate and multivariate statistical process control methods have been widely applied in process industries for early fault detection and localization.The primary objective of the proposed research is the design of an anomaly detection and visualization tool that is able to present to the shift operator – and to the various levels of plant operation and company management – an early, global, accurate and consolidated presentation of the operation of major subgroups or of the whole plant, aided by a graphical form.Piecewise Aggregate Approximation (PAA) and Symbolic Aggregate Approximation (SAX) are considered as two of the most popular representations for time series data mining, including clustering, classification, pattern discovery and visualization in time series datasets. However SAX is preferred since it is able to transform a time series into a set of discrete symbols, e.g. into alphabet letters, being thus far more appropriate for a graphical representation of the corresponding information, especially for the shift operator. The methods are applied on individual time records of each process variable, as well as on entire groups of time records of process variables in combination with Hidden Markov Models. In this way, the proposed visualization tool is not only associated with a process defect, but it allows also identifying which specific abnormal situation occurred and if this has also occurred in the past. Case studies based on the benchmark Tennessee Eastman process demonstrate the effectiveness of the proposed approach. The results indicate that the proposed visualization tool captures meaningful information hidden in the observations and shows superior monitoring performance.