TCBR-HMM: An HMM-based text classifier with a CBR system

This paper presents an innovative solution to model distributed adaptive systems in biomedical environments. We present an original TCBR-HMM (Text Case Based Reasoning-Hidden Markov Model) for biomedical text classification based on document content. The main goal is to propose a more effective classifier than current methods in this environment where the model needs to be adapted to new documents in an iterative learning frame. To demonstrate its achievement, we include a set of experiments, which have been performed on OSHUMED corpus. Our classifier is compared with Naive Bayes and SVM techniques, commonly used in text classification tasks. The results suggest that the TCBR-HMM Model is indeed more suitable for document classification. The model is empirically and statistically comparable to the SVM classifier and outperforms it in terms of time efficiency.     

Model checking temporal knowledge and commitments in multi-agent systems using reduction

Though modeling and verifying Multi-Agent Systems (MASs) have long been under study, there are still challenges when many different aspects need to be considered simultaneously. In fact, various frameworks have been carried out for modeling and verifying MASs with respect to knowledge and social commitments independently. However, considering them under the same framework still needs further investigation, particularly from the verification perspective. In this article, we present a new technique for model checking the logic of knowledge and commitments (CTLKC⁺). The proposed technique is fully-automatic and reduction-based in which we transform the problem of model checking CTLKC⁺ into the problem of model checking an existing logic of action called ARCTL. Concretely, we construct a set of transformation rules to formally reduce the CTLKC⁺ model into an ARCTL model and CTLKC⁺ formulae into ARCTL formulae to get benefit from the extended version of NuSMV symbolic model checker of ARCTL. Compared to a recent approach that reduces the problem of model checking CTLKC⁺ to another logic of action called GCTL¹, our technique has better scalability and efficiency. We also analyze the complexity of the proposed model checking technique. The results of this analysis reveal that the complexity of our reduction-based procedure is PSPACE-complete for local concurrent programs with respect to the size of these programs and the length of the formula being checked. From the time perspective, we prove that the complexity of the proposed approach is P-complete with regard to the size of the model and length of the formula, which makes it efficient. Finally, we implement our model checking approach on top of extended NuSMV and report verification results for the verification of the NetBill protocol, taken from business domain, against some desirable properties. The obtained results show the effectiveness of our model checking approach when the system scales up.     

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.     

青年医学工作者科普能力培养新模式

为了培养青年医师运用医学科普语言传播医学知识的能力，向社会提供更优质、可及的健康知识，改善医患关系，促进社会和谐；同时出于向社区、媒体推送一批优秀青年医学科普人才的考虑，本文在总结北京协和医院培养青年医务人员医学科普能力经验的基础上，尝试构建一套适合大型公立医院（尤其是教学医院）培养青年医务人员医学科普能力的新模式——“科普训练营”。本文旨在系统介绍该模式的产生背景、实践经验及初期效果，阐释实施后的重要意义，及实施过程中的挑战与应对策略。     

探讨加强质量监督管理提高电网安全水平

电网的安全水平主要取决于其使用产品的质量是否过关。如果产品的质量较好，则能建造出优质的电网，电网的安全水平便会随之提高。因此，应加强对产品质量的监督管理，从而提高电网的安全水平。我们可建立质量监督管理系统，及时抽检出质量不过关的产品，从而消除电网运行过程中潜在的安全隐患。     

Thermal imaging of time-varying longitudinal defects in the internal coating of a tube

We deal with the mathematical model of the incremental degradation of the internal coating (e.g. a polymeric material) of a metallic pipe in which a fluid flows relatively fast. The fluid drags solid impurities so that longitudinal scratches, inaccessible to any direct inspection procedure, are produced on the coating. Time evolution of this kind of defects can be reconstructed from the knowledge of a sequence of temperature maps of the external surface. The time-varying orthogonal section of this damaged interface is determined as a function of time and polar angle through the identification of a suitable effective heat transfer coefficient by means of Thin Plate Approximation.     

快速灵敏的LC-MS/MS法测定人血浆中阿莫西林并应用于两种制剂的一致性评价

目的: 建立快速灵敏的LC-MS/MS法测定人血浆中阿莫西林浓度，并用于两种阿莫西林胶囊的一致性评价。方法: 采用岛津公司LCMS-8060型LC-MS/MS仪，以MRM模式测定阿莫西林（m/z 366.00/114.00）的浓度，d4-阿莫西林作内标（m/z 370.10/114.05），离子源为ESI源。色谱柱选用Waters ACQUITY BEH C18（2.1×50 mm，1.7 μm），梯度洗脱。血浆样本加入内标，经甲醇沉淀蛋白后取上清液进样检测。结果: 所建方法经验证，其线性、准确度、精密度、最低定量限、提取回收率、特异性、基质效应、稳定性等各项指标均符合CFDA的指导原则及最新核查标准要求，并较文献报道中的方法有处理简单、灵敏度高、色谱峰形好的优点。结论: 所建方法快速、灵敏，适用于人血浆中阿莫西林浓度的检测。用于一致性评价的样本实测，两种制剂生物等效。     

Cloud based cyber-physical systems: Network evaluation study

In recent years, the Industry 4.0 concept brings new demands and trends in different areas; one of them is distributing computational power to the cloud. This concept also introduced the Reference Architectural Model for Industry 4.0 (RAMI 4.0). The efficiency of data communications within the RAMI 4.0 model is a critical issue. Aiming to evaluate the efficiency of data communication in the Cloud Based Cyber-Physical Systems (CB-CPS), this study analyzes the periods and data amount required to communicate with individual hierarchy levels of the RAMI 4.0 model. The evaluation of the network properties of the communication protocols eligible for CB-CPS is presented. The network properties to different cloud providers and data centers’ locations have been measured and interpreted. To test the findings, an architecture for cloud control of laboratory model was proposed. It was found that the time of the day; the day of the week; and data center utilization have a negligible impact on latency. The most significant impact lies in the data center distance and the speed of the communication channel. Moreover, the communication protocol also has impact on the latency. The feasibility of controlling each level of RAMI 4.0 through cloud services was investigated. Experimental results showed that control is possible in many solutions, but these solutions mostly cannot depend just on cloud services. The intelligence on the edge of the network will play a significant role. The main contribution is a thorough evaluation of different cloud providers, locations, and communication protocols to provide recommendations sufficient for different levels of the RAMI 4.0 architecture.