Distance education is popular worldwide, especially after the COVID-19 pandemic. Assessing the affective domain of distance education becomes challenging because the instructor cannot observe the student's behavior. This article proposes an assessment of the affective domain for distance education systems implemented with big data technologies. An assessment model called AMADEUS has been developed. Exploratory factor analysis (EFA) was used to explore assessment factors and formulate the model. Then, the constructed model was verified by confirmatory factor analysis (CFA). AMADEUS consists of 12 factors in 4 components: responsibility, interest in course material, class participation, and honesty. The experimental results indicated that AMADEUS was consistent with the empirical data and passed all criteria for consideration. After that, an assessment and reporting tool called MOZART has been developed. MOZART employed the AMADEUS model to assess students' affective domain from log files using Hadoop and ELK stack technologies. The MOZART usability assessment results are at a good level in all aspects.

The number of processors embedded on high performance computing platforms is continuously increasing to accommodate user desire to solve larger and more complex problems. However, as the number of components increases, so does the probability of failure. Thus, both scalable and fault-tolerance of software are important issues in this field. To ensure reliability of the software especially under the failure circumstance, the reliability analysis is needed. The discrete-event simulation technique offers an attractive a ternative to traditional Markovian-based analytical models, which often have an intractably large state space. In this paper, we analyze reliability of a self-healing network developed for parallel runtime environments using discrete-event simulation. The network is designed to support transmission of messages across multiple nodes and at the same time, to protect against node and process failures. Results demonstrate the flexibility of a discrete-event simulation approach for studying the network behavior under failure conditions and various protocol parameters, message types, and routing algorithms.

A circulant graph with n nodes andjumpsj1, j2,..., jmis a graph in which each node i, 0 les i les n-1, is adjacent to all the vertices i plusmn jkmodn, where 1 les k les m. A binomial graph network (BMG) is a circulant graph where jk is the power of 2 that is less than or equal to n. This paper presents an optimal (shortest path) two-terminal routing algorithm for BMG networks. This algorithm uses only the destination address to determine the next hop in order to stay on the shortest path. Unlike the original algorithms, it does not require extra space for routing tables or additional information in the packet. The experimental results show that the new optimal algorithm is significantly faster than the original optimal algorithm.

As the number of processors in today's high performance computers continues to grow, the mean-time-to-failure of these computers are becoming significantly shorter than the execution time of many current high performance computing applications. Although today's architectures are usually robust enough to survive node failures without suffering complete system failure, most today's high performance computing applications can not survive node failures and, therefore, whenever a node fails, have to abort themselves and restart from the beginning or a stable-storage-based checkpoint.This paper explores the use of the floating-point arithmetic coding approach to build fault survivable high performance computing applications so that they can adapt to node failures without aborting themselves. Despite the use of erasure codes over Galois field has been theoretically attempted before in diskless checkpointing, few actual implementations exist. This probably derives from concerns related to both the efficiency and the complexity of implementing such codes in high performance computing applications. In this paper, we introduce the simple but efficient floating-point arithmetic coding approach into diskless checkpointing and address the associated round-off error issue. We also implement a floating-point arithmetic version of the Reed-Solomon coding scheme into a conjugate gradient equation solver and evaluate both the performance and the numerical impact of this scheme. Experimental results demonstrate that the proposed floating-point arithmetic coding approach is able to survive a small number of simultaneous node failures with low performance overhead and little numerical impact.