Process Mining of Programmable Logic Controllers: Input/Output Event Logs

This paper presents an approach to model an unknown Ladder Logic based Programmable Logic Controller (PLC) program consisting of Boolean logic and counters using Process Mining techniques. First, we tap the inputs and outputs of a PLC to create a data flow log. Second, we propose a method to translate the obtained data flow log to an event log suitable for Process Mining. In a third step, we propose a hybrid Petri net (PN) and neural network approach to approximate the logic of the actual underlying PLC program. We demonstrate the applicability of our proposed approach on a case study with three simulated scenarios

Adversarial Attacks on Time Series

Time series classification models have been garnering significant importance in the research community. However, not much research has been done on generating adversarial samples for these models. These adversarial samples can become a security concern. In this paper, we propose utilizing an adversarial transformation network (ATN) on a distilled model to attack various time series classification models. The proposed attack on the classification model utilizes a distilled model as a surrogate that mimics the behavior of the attacked classical time series classification models. Our proposed methodology is applied onto 1-Nearest Neighbor Dynamic Time Warping (1-NN ) DTW, a Fully Connected Network and a Fully Convolutional Network (FCN), all of which are trained on 42 University of California Riverside (UCR) datasets. In this paper, we show both models were susceptible to attacks on all 42 datasets. To the best of our knowledge, such an attack on time series classification models has never been done before. Finally, we recommend future researchers that develop time series classification models to incorporating adversarial data samples into their training data sets to improve resilience on adversarial samples and to consider model robustness as an evaluative metric.Comment: 13 pages, 7 figures, 6 table

A Faculty Retreat Model Featuring Collaborative and Active Learning

A workshop-style, active-learning model was recently implemented in a Mechanical and Industrial Engineering (MIE) department retreat prior to the start of the Fall 2018 term. The department is currently undergoing a curriculum redesign, and a special committee was created to design the talking points for the retreat. Among the concerns were: meaning of grades, expectation of grade distribution, adoption of teaching pedagogies that align with the department goals, and definition of teaching excellence. Opinions were divided, and many felt strongly about each topic. New and non-tenure-track faculty were initially assigned as scribe or presenter, so as to encourage participation. A moderator in each group helped keep the conversation on track, and intervened whenever necessary. A preliminary post-retreat evaluation of faculty satisfaction shows encouraging results. A follow-up dissemination of the retreat outcome took place during a regular faculty meeting several weeks after the retreat, and the discussion topics were revisited in an attempt to reach a consensus, particularly regarding issues that were divisive. Future work include a second follow-up meeting and creation of a task force to act upon the retreat outcomes

A Critical Look at Mechanical Engineering Curriculum: Assessing the Need

Since the Morrill Land-Grant Colleges Act in 1862, the U.S. higher education system has been serving the industrial world, and engineering study is the epitome of this ideal: Serve those who will practice it in the immediate future. The mechanical engineering curricula have long been evolving to meet the demand of the changing economy, and it may soon be due for a major update. This paper aims to present an initial effort to explore the need for a systematic redesign, or reform, of the mechanical engineering curriculum at [Institution X], where curricular changes during the past five decades have been largely isolated, incremental and piecemeal