Model repair — aligning process models to reality

Process mining techniques relate observed behavior (i.e., event logs) to modeled behavior (e.g., a BPMN model or a Petri net). Process models can be discovered from event logs and conformance checking techniques can be used to detect and diagnose differences between observed and modeled behavior. Existing process mining techniques can only uncover these differences, but the actual repair of the model is left to the user and is not supported. In this paper we investigate the problem of repairing a process model w.r.t. a log such that the resulting model can replay the log (i.e., conforms to it) and is as similar as possible to the original model. To solve the problem, we use an existing conformance checker that aligns the runs of the given process model to the traces in the log. Based on this information, we decompose the log into several sublogs of non-fitting subtraces. For each sublog, either a loop is discovered that can replay the sublog or a subprocess is derived that is then added to the original model at the appropriate location. The approach is implemented in the process mining toolkit ProM and has been validated on logs and models from several Dutch municipalities.     

An overview on fault diagnosis and nature-inspired optimal control of industrial process applications

Fault detection, isolation and optimal control have long been applied to industry. These techniques have proven various successful theoretical results and industrial applications. Fault diagnosis is considered as the merge of fault detection (that indicates if there is a fault) and fault isolation (that determines where the fault is), and it has important effects on the operation of complex dynamical systems specific to modern industry applications such as industrial electronics, business management systems, energy, and public sectors. Since the resources are always limited in real-world industrial applications, the solutions to optimally use them under various constraints are of high actuality. In this context, the optimal tuning of linear and nonlinear controllers is a systematic way to meet the performance specifications expressed as optimization problems that target the minimization of integral- or sum-type objective functions, where the tuning parameters of the controllers are the vector variables of the objective functions. The nature-inspired optimization algorithms give efficient solutions to such optimization problems. This paper presents an overview on recent developments in machine learning, data mining and evolving soft computing techniques for fault diagnosis and on nature-inspired optimal control. The generic theory is discussed along with illustrative industrial process applications that include a real liquid level control application, wind turbines and a nonlinear servo system. New research challenges with strong industrial impact are highlighted.     

A novel approach to adaptive relational association rule mining

The paper focuses on the adaptive relational association rule mining problem. Relational association rules represent a particular type of association rules which describe frequent relations that occur between the features characterizing the instances within a data set. We aim at re-mining an object set, previously mined, when the feature set characterizing the objects increases. An adaptive relational association rule method, based on the discovery of interesting relational association rules, is proposed. This method, called ARARM (Adaptive Relational Association Rule Mining) adapts the set of rules that was established by mining the data before the feature set changed, preserving the completeness. We aim to reach the result more efficiently than running the mining algorithm again from scratch on the feature-extended object set. Experiments testing the method's performance on several case studies are also reported. The obtained results highlight the efficiency of the ARARM method and confirm the potential of our proposal.     

Geothermal energy utilization trends from a technological paradigm perspective

The use of geothermal energy and its associated technologies has been increasing worldwide. However, there has been little paradigmatic research conducted in this area. This paper proposes a systematic methodology to research the development trends for the sustainable development of geothermal energy. A novel data analysis system was created to research the geothermal energy utilization trends, and a technological paradigm theory was adopted to explain the technological changes. A diffusion velocity model was used to simulate and forecast the geothermal power generation development in the diffusion phase. Simulation results showed that the development of installed capacity for geothermal generation had a strong inertia force along with the S-curve. Power generation from geothermal power sources reached a peak in 2008 and is estimated to be saturated by 2030. Geothermal energy technologies in hybrid power systems based on other renewable energy sources look to be more promising in the future.     

循环伏安法在润滑油检测中的应用

介绍了循环伏安法的产生背景、原理。应用该技术可以快速、方便地对润滑油中抗氧剂、总酸（碱）值进行测定，并且可以对不同厂家润滑油的抗氧剂包进行区别。该技术还可以有效地评价润滑油的使用寿命和设备工作状况。     

原油基压裂液研究

研制了一种适用于低压、低渗、水敏性储集层的新型原油基压裂液体系。根据基液原油的组分合成相应的增稠剂，增稠剂在原油中与交联剂反应，形成网状结构，使原油成为黏度可以调控的冻胶，从根本上改变了油基压裂液以柴油、煤油为基液的现状，降低了油基压裂液的成本，同时还提高了压裂液的抗温、抗剪切和破胶性能，并将交联时间缩短到2h以内，可以满足现场压裂施工的要求，大大降低了施工强度和压裂改造的综合成本。在青海油田进行的现场先导试验取得成功。图9表1参5     

USERS' TWO-DIMENSIONAL INTEREST AND ITS STORAGE METHOD

The users' interest can be mined from the web cache and can be used widely. The interest can be specialized by the two-tuple (term, weight) in the simple interest model, in which the association relations are not mined, and then the interest cannot be associated in expressing the users' interest. Based on analyzing the WWW cache model, this letter brings forward a two-dimensional interest model and gives the interrelated methods on how to store the two-dimensional interest model effectively.     

Improving Wear Resistance of the Ni-base Thermal Spray-Welding Coating Using Rare Earths

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秸杆材料用作草皮栽培基质的研究

本文介绍了秸杆毡的成型工艺 ,通过植物所需的水、肥料和空气三种因素对秸杆毡的化学和物理性能进行了研究 ,该材料可被用作草皮栽培基质     

莺-琼盆地生物气及生物—低成熟过渡带气特征与勘探前景

莺 琼盆地天然气资源丰富 ,天然气成因类型多 ,迄今为止 ,除在该区浅层和中深层发现以成熟—高成熟的热成因腐殖型气 (煤型气 )为主的天然气藏外 ,也发现了一些生物气及生物—低成熟过渡带气气藏 ,且均具较高的产量和一定的储量规模 ,其勘探前景广阔。