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Data reconciliation and gross error detection are traditional methods toward detecting mass balance inconsistency within process instrument data. These methods use a static approach for statistical evaluation. This thesis is concerned with using an alternative statistical approach (Bayesian statistics) to detect mass balance inconsistency in real time. The proposed dynamic Baysian solution makes use of a state space process model which incorporates mass balance relationships so that a governing set of mass balance variables can be estimated using a Kalman filter. Due to the incorporation of mass balances, many model parameters are defined by first principles. However, some parameters, namely the observation and state covariance matrices, need to be estimated from process data before the dynamic Bayesian methods could be applied. This thesis makes use of Bayesian machine learning techniques to estimate these parameters, separating process disturbances from instrument measurement noise. / Process Control

When video transmits over error-prone channels, the fragile property of compressed stream makes it sensitive to bit error. Often even a slight error can make video unable to correctly decode. Therefore, there is a need for a good error control method to solve the problem. This paper presents a novel error detection and concealment strategy along with watermark technique. The proposed watermark-based scheme utilizes two kinds of watermark technique, a fragile watermark is used to detect and localize errors, and a robust watermark is used to reconstruct error areas when errors exist. Experimental results show the proposed watermark-based scheme has good error detection capabilities and complete error recovery information, therefore significant improves video quality after errors happened, especially in the case of higher loss probabilities.

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Introduction: This thesis hypothesized that synchronous feedback which is supportive in nature would have a positive impact on the learning and transfer of the skills of visual and auditory cue identification in osteopathic diagnostic procedures. It was believed that the positive impact of supportive feedback would be evident through accurate identification of both visual and auditory cues. The categories of cues were visually identifiable asymmetrical motion, visual or auditory expressions of pain, and visually identifiable cues of a possible soft tissue tear or motor nerve issue. Methods: All participants received the same video-based learning resource which was optimized for content (what/how) and cognition (why) followed by the same instructions for the practice phase. During the practice phase all participants were shown a video of a previously learned diagnostic procedure which contained visual and auditory cues. Between videos, participants were all asked the same questions in the same order. In the Supportive Feedback with Specific Content (SC) group participants would receive supportive comments regardless of accuracy of answers and, if they had identified an appropriate physical phenomenon but ascribed it to an incorrect category, they would receive feedback to correct the categorization error. The Supportive Feedback (S) group would receive supportive comments regardless of accuracy of answers but no feedback in relation to categorization errors. The No Feedback (NF) group would receive no supportive comments or feedback in relation to categorization errors. Responses were coded as accurate detection of cues, or categorization errors (detection of cues that were not there, or incorrect categorization of cues). Results: All groups performed similarly with respect to accurate identification of auditory and visual cues such that there was no identifiable impact in relation to group condition during both the practice and transfer phases. The SC group did commit less categorization errors (11.43%) when compared to the S (28.21%) and NF (31.43%) groups. Conclusion: The experimental findings supported the hypothesis that supportive feedback enhanced learning outcomes. While not demonstrated through accuracy of cue identification, this was demonstrated through a reduction in cue categorization errors. An additional hypothesis generated from the results of this thesis is that educational designs that allow for the commission of errors by learners followed by correction in the form of direct feedback or group lecture may predict faster attainment of expertise as noted in the reduction of errors. / Thesis / Master of Science (MSc) / Synchronous feedback has the ability to aid learning. It was hypothesized in this thesis that synchronous feedback that was supportive in nature would improve learning and transfer for learning the skill of visual and auditory cue identification in osteopathic diagnostic procedures. All participants received the same initial learning material, the same instructions for the practice phase of the experiment, and the same videos of a previously learned diagnostic procedure that they identified visual and diagnostic cues from. During the practice phase the three groups were the Supportive Feedback with Specific Content (SC), Supportive Feedback (S), and No Feedback (NF). The differences between groups were evident between diagnostic videos subsequent to the collection of answers for identified cues. The material differences were the delivery of supportive comments regardless of accuracy of answers (SC and S groups), the delivery of specific feedback when accurate cues were identified but placed in the wrong category (SC group only), or the absence of any commentary (NF group). All groups identified cues at similar levels such that the supportiveness of feedback showed no impact on performance. There was a notable difference between groups in relation to the commission of categorization errors where the SC group made less categorization errors with the S group and NF group committing errors at similar rates. The primary benefit of synchronous feedback in this experiment is that the instructor is able to identify errors and provide insight for correction.