By Roger Lee (eds.)
This edited ebook offers medical result of the 13th IEEE/ACIS overseas convention on machine and data technology (ICIS 2014) which was once hung on June 4-6, 2014 in Taiyuan, China. the purpose of this convention was once to collect researchers and scientists, businessmen and marketers, lecturers, engineers, computing device clients, and scholars to debate the various fields of desktop technology and to proportion their reports and alternate new rules and data in a significant approach. study effects approximately all elements (theory, functions and instruments) of machine and knowledge technology, and to debate the sensible demanding situations encountered alongside the way in which and the suggestions followed to resolve them.
The convention organizers chosen the easiest papers from these papers authorised for presentation on the convention. The papers have been selected in accordance with assessment ratings submitted through individuals of this system committee, and underwent extra rigorous rounds of assessment. This booklet captures 14 of the conference’s so much promising papers, and we impatiently look forward to the $64000 contributions that we all know those authors will carry to the sector of desktop and data science.
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Instead of adding to the already large number of checklists for learning scenario evaluation, we are attempting, in the following section, to address contextual evaluation based on formal modeling and verification of educational scenario. Next, the evaluation framework is discussed. 1 ReStart-Me Challenges In order to fill the gap between learning scenarios evaluation methods and ubiquitous learning scenarios, we present in this paper, a formal method to evaluate scenarios at an early stage: ReStart-Me (Re-engineering educational Scenario based on timed automata and tracks treatment for Malleable learning environment).
Then, we compute the similarity result between the current software vector and the matrices (for source control repositories). Here, we also extract consecutive versions which are related to the current software. Until here, all the related information have been extracted from various SHR. We believe that such a preprocess on  can effectively improve the effectiveness of traditional software maintenance activities which are not preprocessed or filtered. 4 Evaluation Our approach aims to improve traditional SHR-based software maintenance techniques after filtering the unrelated information without decreasing the completeness of the results.
Dependability requirements and test cases are modeled into timed automata. Then, they are transformed into temporal logical properties to formal checking methods. The evaluation process contains essentially these three steps (see Fig. 2) inspired from : • Step 0: Behavioural Modeling: This phase provides informal or/and semiformal descriptions of both the learning environment and the correctness properties to be checked. Pedagogues and designers have to participate in this phase. • Step 1: Formal Modeling of Educational Scenario: In this step, conceptual designers identify the entities to be considered.
Computer and Information Science by Roger Lee (eds.)