RULES BASED MODELING OF DISCRETE EVENT SYSTEMS WITH FAULTS AND THEIR DIAGNOSIS

Failure diagnosis in large and complex systems is a critical task. In the realm of discrete event systems, Sampath et al. proposed a language based failure diagnosis approach. They introduced the diagnosability for discrete event systems and gave a method for testing the diagnosability by first constructing a diagnoser for the system. The complexity of this method of testing diagnosability is exponential in the number of states of the system and doubly exponential in the number of failure types. In this thesis, we give an algorithm for testing diagnosability that does not construct a diagnoser for the system, and its complexity is of 4th order in the number of states of the system and linear in the number of the failure types. In this dissertation we also study diagnosis of discrete event systems (DESs) modeled in the rule-based modeling formalism introduced in [12] to model failure-prone systems. The results have been represented in [43]. An attractive feature of rule-based model is it\u27s compactness (size is polynomial in number of signals). A motivation for the work presented is to develop failure diagnosis techniques that are able to exploit this compactness. In this regard, we develop symbolic techniques for testing diagnosability and computing a diagnoser. Diagnosability test is shown to be an instance of 1st order temporal logic model-checking. An on-line algorithm for diagnosersynthesis is obtained by using predicates and predicate transformers. We demonstrate our approach by applying it to modeling and diagnosis of a part of the assembly-line. When the system is found to be not diagnosable, we use sensor refinement and sensor augmentation to make the system diagnosable. In this dissertation, a controller is also extracted from the maximally permissive supervisor for the purpose of implementing the control by selecting, when possible, only one controllable event from among the ones allowed by the supervisor for the assembly line in automaton models

Dynamic merge clustering algorithm and its application in evaluation of the regional scientific and technological innovation capability

Cluster analysis is an important part of study and application in data mining and hierarchical clustering is currently the most widely used clustering method. A dynamic clustering algorithm named DCMA was proposed based on the defects of hierarchical clustering method. The irreversibility and the indispensable process ending condition of specifying the desired number of clusters and threshold adopts clusters diversity to automatically merge and divide the clusters. And clustering analysis and comprehensive evaluation were conducted to test the scientific and technological innovation capacity of 13 prefecture-level cities of Jiangsu Province. Results verified the feasibility and effectiveness of the proposed method. Data processing results show that this method can provide a scientific quantitative decision-making evaluation model for the relevant administrative departments

Rules-based Modeling of an Assembly Line and its Diagnosis

We study diagnosis of an assembly-line [13] that is modeled in the rules-based modeling formalism introduced in [7], and later extended in [14] to model failure-prone systems. An attractive feature of rules-based model is it’s compactness (size of the model is polynomial in number of input and output signals). A motivation for the work presented in [15] is to develop failure diagnosis techniques that can exploit this compactness. In order to demonstrate the usefulness of the rules-based model and of diagnosis techniques based on such a model in manufacturing systems, an educational test-bed that simulates an automated car assembly-line built using LEGO r ○ blocks is being employed. An automaton model based control of this system was presented in [13]. In this paper we provide a rules-based model of the assembly-line. Next we demonstrate the diagnosis technique for a rules-based model, that is based on 1 st-order temporal logic model checking [15], by applying it to a part of the assembly-line. When the system is found to be not diagnosable, we use sensor refinement and sensor augmentation to make the system diagnosable

Online teaching: are we alienating our Asian students?: a case study

This paper has emerged from an ongoing research project investigating the policy, behavioural and curricular issues associated with the online educational experience of Asian university students studying onshore in Australia. Two key perceptions have surfaced. First, that these students are uncomfortable with learning in online mode, despite their familiarity with computers and information technology. Second, that their command of English is a factor with debate over whether they would feel more comfortable engaging in learning activities in a class-based face-to-face context than in online mode. Arguably, while important, these concerns are symptoms of a broader problem, which may have to do with cultural and behavioural considerations both in Australia and the home country. This paper seeks to identify these underlying causes and propose potential solutions to the problems of online education. The research employs mixed methods, qualitative and quantitative and combines a descriptive and exploratory approach using both primary and secondary data sources. The major findings are drawn from a threeyear, in-depth case study of an online educational initiative for onshore Asian students at Swinburne University of Technology. Our findings confirm that, although Asian student enrolments remain stable, there is indeed an undercurrent of discontent with online delivery among onshore Asian students. There is also evidence that the success rate of students in face-to-face classes is well in excess of that for online classes. However, there is more to this than simply the inappropriateness of online teaching and learning for Asian students. Our research suggests that a more considered and consultative approach that takes more care over deeper cultural concerns and addresses issues around the social as well as the educational environment is likely to dispel most concerns about online education. This could also provide potential solutions for Australian educators seeking to improve the educational experience of onshore Asian students

Automated control synthesis for an assembly line using discrete event system control theory

Abstract — The design of logic controllers for event-driven systems continue to rely largely on intuitive methods rather than on formal techniques. This approach results in a control code that requires extensive verification, is hard to maintain and modify, and may even fail at times. Supervisory control theory (SCT) provides a formal approach to logic control synthesis. In order to demonstrate the usefulness of the supervisory control theory in manufacturing systems, an educational test-bed that simulates an automated car assembly line has been built using LEGO r ○ blocks. Finite state machines (FSMs) are used for modeling operations of the assembly line, and for the specifications that accomplish the task of successfully completing the assembly repeatedly. Using the technique of SCT, we derive a supervisor that enforces the specifications while offering the maximum flexibility of assembly. Subsequently a controller is extracted from the maximally permissive supervisor for the purpose of implementing the control by selecting, when possible, only one controllable event from among the ones allowed by the supervisor. Testing to check the correctness of the control code is reduced, since the controller is guaranteed to enforce the specifications

Negative Control of the Myc Protein by the Stress-Responsive Kinase Pak2

Pak2 is a serine/threonine kinase that participates in the cellular response to stress. Among the potential substrates for Pak2 is the protein Myc, encoded by the proto-oncogene MYC. Here we demonstrate that Pak2 phosphorylates Myc at three sites (T358, S373, and T400) and affects Myc functions both in vitro and in vivo. Phosphorylation at all three residues reduces the binding of Myc to DNA, either by blocking the requisite dimerization with Max (through phosphorylation at S373 and T400) or by interfering directly with binding to DNA (through phosphorylation at T358). Phosphorylation by Pak2 inhibits the ability of Myc to activate transcription, to sustain cellular proliferation, to transform NIH 3T3 cells in culture, and to elicit apoptosis on serum withdrawal. These results indicate that Pak2 is a negative regulator of Myc, suggest that inhibition of Myc plays a role in the cellular response to stress, and raise the possibility that Pak2 may be the product of a tumor suppressor gene

Simulation of Irrigation Strategy Based on Stochastic Rainfall and Evapotranspiration

The North China Plain plays a pivotal role in China’s crop production, contributing to 30% of the maize yield. Nevertheless, summer maize in this region faces challenges due to climatic constraints characterized by concurrent high temperatures and rainfall during the growing season, resulting in a relatively high evapotranspiration rate. In this study, we explored eight soil moisture-based threshold irrigation strategies, consisting of two upper limits and four lower limits, along with a rainfed mode (E). The upper and lower irrigation limits are expressed as a percentage of the field’s water-holding capacity (sfc). For the four full irrigation modes (A1, A2, A3, A4), the lower limits were set at 0.6 sfc, 0.6 sfc, 0.5 sfc, and 0.5 sfc, respectively. The upper limits were defined at two levels: 0.8 sfc for A1 and A2 and sfc for A3 and A4. Similarly, for the four deficit irrigation modes (B1, B2, B3, B4), the lower limits were established at 0.4 sfc, 0.4 sfc, 0.3 sfc, and 0.3 sfc, respectively, with the upper limits set at two levels: 0.8 sfc for B1 and B2 and the full sfc for B3 and B4. To investigate the impact of rainfall and potential evapotranspiration on these irrigation modes under long-term fluctuations, we employed a stochastic framework that probabilistically linked rainfall events and irrigation applications. The Monte Carlo method was employed to simulate a long-term series (4000a) of rainfall parameters and evapotranspiration using 62 years of meteorological data from the Xinxiang region, situated in the southern part of the North China Plain. Results showed that the relative yield and net irrigation water requirement of summer maize decreased with decreasing irrigation lower limits. Additionally, the interannual variation of rainfall parameters and evapotranspiration during the growing season were remarkable, which led to the lowest relative yield of the rainfed mode (E) aligned with a larger interannual difference. According to the simulation results, mode A4 (irrigation lower limit equals 0.5 sfc, irrigation upper limit equals 0.8 sfc) could be adopted for adequate water resources. Conversely, mode B2 is more suitable for a lack of water resources