Social Network Analysis

On Educational psychology: A cognitive view.

THE FIFTH DISCIPLINE The Art & Practice of the Learning Organization

The Cambridge handbook of multimedia learning

https://limlab.ucsf.edu/papers/pdfs/pb_2012.pdf

Systematic Functional Prioritization of Protein Posttranslational Modifications

PSAIA (Protein Structure and Interaction Analyzer) was developed to compute geometric parameters for large sets of protein structures in order to predict and investigate protein-protein interaction sites. In addition to most relevant established algorithms, PSAIA offers a new method PIADA (Protein Interaction Atom Distance Algorithm) for the determination of residue interaction pairs. We found that PIADA produced more satisfactory results than comparable algorithms implemented in PSAIA. Particular advantages of PSAIA include its capacity to combine different methods to detect the locations and types of interactions between residues and its ability, without any further automation steps, to handle large numbers of protein structures and complexes. Generally, the integration of a variety of methods enables PSAIA to offer easier automation of analysis and greater reliability of results. PSAIA can be used either via a graphical user interface or from the command-line. Results are generated in either tabular or XML format. In a straightforward fashion and for large sets of protein structures, PSAIA enables the calculation of protein geometric parameters and the determination of location and type for protein-protein interaction sites. XML formatted output enables easy conversion of results to various formats suitable for statistic analysis. Results from smaller data sets demonstrated the influence of geometry on protein interaction sites. Comprehensive analysis of properties of large data sets lead to new information useful in the prediction of protein-protein interaction sites.

/pdf/psaia-protein-structure-and-interaction-analyzer-vk8mtlc6jr.pdf

PSAIA – Protein Structure and Interaction Analyzer

An efficient real-time implementation of digital filtering algorithms using a multiprocessor system in a ring network is investigated. This method is based on a parallel block processing approach, where a continuously supplied input data is divided into blocks, and the blocks are processed concurrently by being assigned to each processor in the system. This approach requires only a simple interconnection network and reduces significantly the number of communications among the processors, making the system easily expandable and highly efficient. In addition, various digital signal processing algorithms can be implemented on the same multiprocessor system. The data dependency of the blocks to be processed concurrently brings on dependency problems between the processors. A systematic scheduling method has been developed by using a precedence graph for the analysis of the dependency relation. Methods for solving the dependency problems between the processors are also investigated. Implementation procedures and results for FIR, recursive, and adaptive filtering algorithms are illustrated. >

Multiprocessor implementation of digital filtering algorithms using a parallel block processing method

This study aimed to investigate the effects of using online formative assessments on students’ learning achievements. Using a quasi-experimental study design with one control group (no formative assessments available), and two experimental groups receiving feedback in available online formative assessments (knowledge of the correct response – KCR, or elaborated feedback – EF), it was investigated how feedback type in combination with learning content complexity will affect students’ learning achievements when used in-vivo, in a digital signal processing university course. Data generated by the two experimental groups was additionally used to investigate differences in using online formative assessments based on the feedback type. Study findings suggest online formative assessments are a very efficient educational intervention for this domain. The acquired data suggests that students quickly recognized the value of the formative assessments and that more than 90% of students have used them extensively. Statistically significant improvements in learning achievements were observed in the KCR group compared to the control group (p < 0.01, Cohen’s d between 0.691 and 1.080, depending on the learning content complexity), and KCR group compared to the EF group (p < 0.01, Cohen’s d = 0.877, in the case of most complex of the three learning contents used). No statistically significant differences were found in formative assessment usage between the two experimental groups, aside from the difference in the time between consecutive formative assessment attempts, indicating students did make use of the available feedback. Reported results are significant for demonstrating the potential of online formative assessments in achieving the desired learning outcomes in higher education, as well as for gaining insights into students’ habits of using them.

Online formative assessments in a digital signal processing course: Effects of feedback type and content difficulty on students learning achievements

There is a large variety of lecture capture forms being used today when considering their content and ways in which that content is being reproduced. The objective of this study was therefore to investigate the students' perception and the learning potential of lecture captures enriched using additional learning contents compared to lecture captures containing only the video and audio recording of the lecturer and his slideshow. In an experiment in which students were learning using each of those two types of learning materials, a slight yet unsignificant difference was observed in favour of learning from rich lecture captures. Students' survey responses indicated they prefer rich lecture captures for learning and that their availability would not necessarily have a negative impact on students' live lecture attendance rates. These results suggest that even though students prefer rich lecture capture materials for learning, they did not prove to be more efficient in achieving the desired learning outcomes. Additional research would be needed to verify this conclusion on more complex subjects.

Assessing the learning potential and students' perception of rich lecture captures

This paper deals with the asynchronous model which we have developed for distance learning. All lectures have been recorded and a multimedia has been made on CD ROM as a combination of lectures in Power Point, simulations in Matlab, animation, video and speech. Apart from those on CD ROM, the material is available to the students through Internet: lectures, drill sessions, tests, quizzes. Laboratory sessions have also been organized through asynchronous distance learning. This kind of teaching organization enables both the students and the professors not to be tied to a fixed place and time, while being in contact at any time. Asynchonous distance learning is going to be described in all its integral parts, its results and both the advantages and disadvantages of this model.

/pdf/asynchronous-distance-learning-model-adl-4ky1fgje2o.pdf

Branko Jeren

Papers

PSAIA – Protein Structure and Interaction Analyzer

Multiprocessor implementation of digital filtering algorithms using a parallel block processing method

Online formative assessments in a digital signal processing course: Effects of feedback type and content difficulty on students learning achievements

Assessing the learning potential and students' perception of rich lecture captures

Asynchronous Distance Learning Model (ADL)