Formal features as a design factor of video segments in interactive video programmes

Video segments may be characterized by formal design features with respect to factors such as complexity of narration, mutual influence of picture and sound, use of superimposed texts, information load due to technical terms, and animation. The paper suggests ways to operationalize these factors and reports about an experiment in which the influence of these formal features was studied with respect to perceived information load of video segments by learners. The length of a segment was thereby counted as the number of information elements it contains. An information element is defined as one uninterrupted statement of the narrator about which one factual question can be presented. The experiment was carried out by using an experimental videodisc programme about cheesemaking that contains 252 information elements which form a connected discourse of 36 min if the programme is played linearly without stopping. Subjects had the task to divide this programme into segments by deciding for themselves how often they would stop before completing the programme. At every stopping place, the subjects were questioned about the content of the just completed segment.\ud \ud The results of the experiment suggest that: (a) subjects tend to perceive narrated sentences as one whole, regardless of the number of facts implied, (b) content-related technical terms seem not to determine difficulty level, (c) superimposed texts show a trend to help subjects who prefer short segments to choose longer segments and subjects who prefer long segments to choose shorter segments, (d) animation is positively (but moderately) correlated with mean self-chosen segment length

Effects of Teaching Strategies in Annotated Bibliography Writing

The study examines the effect of teaching strategies to improved writing of students in the tertiary level. Specifically, three teaching approaches – the use of modelling, grammar-based, and information element-focused – were tested on their effect on the writing of annotated bibliography in three  research classes at a university in Manila. Initially, 125 participants from the three classes were administered a pre-test to check their writing proficiency. Each class was then exposed to a particular teaching approach. All participants were instructed to write an annotated bibliography right after. All annotated bibliographies were rated using one assessment scale. Descriptive statistics as well as Pearson correlations were obtained. Using One-Way ANOVA, the study revealed that the  modelling approach has the most marked effect on the success of annotated bibliography writing. The findings in the study may be used by teachers to guide them in their research writing course. The study has impact on the way educators should present their learning materials for the students’ more improved  writing of annotated bibliography. Keywords: modelling, grammar-based, information element-focused, annotated bibliograph

MDS Array Codes with Optimal Rebuilding

MDS array codes are widely used in storage systems to protect data against erasures. We address the rebuilding ratio problem, namely, in the case of erasures, what is the the fraction of the remaining information that needs to be accessed in order to rebuild exactly the lost information? It is clear that when the number of erasures equals the maximum number of erasures that an MDS code can correct then the rebuilding ratio is 1 (access all the remaining information). However, the interesting (and more practical) case is when the number of erasures is smaller than the erasure correcting capability of the code. For example, consider an MDS code that can correct two erasures: What is the smallest amount of information that one needs to access in order to correct a single erasure? Previous work showed that the rebuilding ratio is bounded between 1/2 and 3/4 , however, the exact value was left as an open problem. In this paper, we solve this open problem and prove that for the case of a single erasure with a 2-erasure correcting code, the rebuilding ratio is 1/2 . In general, we construct a new family of r-erasure correcting MDS array codes that has optimal rebuilding ratio of 1/r in the case of a single erasure. Our array codes have efficient encoding and decoding algorithms (for the case r = 2 they use a finite field of size 3) and an optimal update property

Optimal Rebuilding of Multiple Erasures in MDS Codes

MDS array codes are widely used in storage systems due to their computationally efficient encoding and decoding procedures. An MDS code with $r$ redundancy nodes can correct any $r$ node erasures by accessing all the remaining information in the surviving nodes. However, in practice, $e$ erasures is a more likely failure event, for $1\le e<r$. Hence, a natural question is how much information do we need to access in order to rebuild $e$ storage nodes? We define the rebuilding ratio as the fraction of remaining information accessed during the rebuilding of $e$ erasures. In our previous work we constructed MDS codes, called zigzag codes, that achieve the optimal rebuilding ratio of $1/r$ for the rebuilding of any systematic node when $e=1$, however, all the information needs to be accessed for the rebuilding of the parity node erasure. The (normalized) repair bandwidth is defined as the fraction of information transmitted from the remaining nodes during the rebuilding process. For codes that are not necessarily MDS, Dimakis et al. proposed the regenerating codes framework where any $r$ erasures can be corrected by accessing some of the remaining information, and any $e=1$ erasure can be rebuilt from some subsets of surviving nodes with optimal repair bandwidth. In this work, we study 3 questions on rebuilding of codes: (i) We show a fundamental trade-off between the storage size of the node and the repair bandwidth similar to the regenerating codes framework, and show that zigzag codes achieve the optimal rebuilding ratio of $e/r$ for MDS codes, for any $1\le e\le r$. (ii) We construct systematic codes that achieve optimal rebuilding ratio of $1/r$, for any systematic or parity node erasure. (iii) We present error correction algorithms for zigzag codes, and in particular demonstrate how these codes can be corrected beyond their minimum Hamming distances.Comment: There is an overlap of this work with our two previous submissions: Zigzag Codes: MDS Array Codes with Optimal Rebuilding; On Codes for Optimal Rebuilding Access. arXiv admin note: text overlap with arXiv:1112.037

Derivation of diagnostic models based on formalized process knowledge

© IFAC.Industrial systems are vulnerable to faults. Early and accurate detection and diagnosis in production systems can minimize down-time, increase the safety of the plant operation, and reduce manufacturing costs. Knowledge- and model-based approaches to automated fault detection and diagnosis have been demonstrated to be suitable for fault cause analysis within a broad range of industrial processes and research case studies. However, the implementation of these methods demands a complex and error-prone development phase, especially due to the extensive efforts required during the derivation of models and their respective validation. In an effort to reduce such modeling complexity, this paper presents a structured causal modeling approach to supporting the derivation of diagnostic models based on formalized process knowledge. The method described herein exploits the Formalized Process Description Guideline VDI/VDE 3682 to establish causal relations among key-process variables, develops an extension of the Signed Digraph model combined with the use of fuzzy set theory to allow more accurate causality descriptions, and proposes a representation of the resulting diagnostic model in CAEX/AutomationML targeting dynamic data access, portability, and seamless information exchange