Tests are a source of anxiety and have proved to impact the grades among students. In addition, students do not have the time to prepare for their exams. The ultimate goal of the instructor is to create and offer an environment that reduces the examination stress while maximizes learning in the little time available to the students. The demand on students’ available time is a major challenge. Although active learning has been utilized to increase student engagement and ultimately increase learning, it has never been used to reduce the test anxiety, increase learning in relation to available-student-time or attempt to increase learning with respect to available student time. Student time has been recognized as the most precious resource in learning. This paper proposes a mechanism of active learning, when employed can create an environment for less stressful exam taking while boosting and amplifying learning in a limited amount of time. Various pedagogical and psychological theories have been explored to develop this methodology that has been employed in three different semesters. The results have shown that students prefer this less stressful mechanism of testing and improved learning and students have commented that they felt they were on top of the materials being covered in class throughout the year and felt prepared for the final with little or no preparation for the final exam. In addition, students felt reduced stress during the test taking.

Assessment of education is the standardization imposed by the government to be followed by all universities in Indonesia. Fulfillment of national standards of education aims to ensure quality higher education practices and the quality of its graduates, One of the education practices assessment are assessment of the ratio of lecturers to students. This study aims to help the managerial prepare lecturers to facilitate the process of education and the accreditation process to be faced. Model used with expert system for its inferencing engine with the help of ARIMA forecasting algorithm to predict until the period of accreditation, Forecasting results show the model (1,1,0) which is eligible for prediction.

Data mining or the discovery of knowledge out of databases extracts patterns, and useful and non-substantial, implicit, and unknown information from large databases. Searching for associative rules is a data mining method where relationships and dependencies Interactions between a large set of data items are shown. In large organizations, most data are created at the passage of time. Relational tables in a variety of business or scientific domains have rich information, with high quantative and nominal data types. Therefore, in order to gather information, measure performance and increase business efficiency, it is necessary to isolate relational database and store data in a data warehouse. Using the multidimensional data mining that integrates online analytical processing with data mining, knowledge can be found in multidimensional databases.
In this article, to avoid inappropriate rules in exploring associative rules, the online analytical processing technique is combined with the Apriori algorithm and explores associative rules on multi-dimensional and multilevel data using the data cubic and Apriori algorithm. In addition, the criteria of accuracy, tool performance, and runtime are defined for comparing techniques for exploring associative rules. The metrics mentioned in the scope of this paper have been compared, and data from the Central Insurance Agency have been analyzed using data cubes and the Apriori algorithm, and useful association rules have been generated. Results of the research displays improvement of the response time compared to the other methods.

The tremendous gain owing to the ubiquitous acceptance of the cloud services across the globe results in more complexity for the cloud providers by way of resource maintenance. This has a direct effect on the cost economy for them if the resources are not efficiently utilized. Most of the allocation strategies follow mechanisms involving direct allotment of VMs onto the servers based on their capabilities. This paper presents a VM allocation strategy that looks at VM placement by allowing server capacity to be partitioned into different classes. The classes are mainly based on the RAM and processing abilities which would be matched with VMs need. When the match is found the servers from this category are provisioned for the task executions. Based on the experimentation for various datacenter scenarios, it has been found that the proposed mechanism results in significant energy savings with reduced response time compared to the traditional VM allocation policies.

This paper presents the use of the FAHPmethod (Fuzzy Analytic Hierarchy Process) to help young people choose the most appropriate activity sectors for their profile. This choice is based on three criteria: Professional interests, professional sub-interests and personality traits. This work is a part of a global context aiming to apply the Multi-criteria Decision-Making (MCDM) methods in the vocational guidance according to the process schematized in Figure 3.

News summarization is a process of distilling the most important information from a news document in a precise way. For the advancement of Internet nowadays almost all of the Bangla newspapers have their online versions, and people of this era like to read newspaper from website using Internet. But large amount of electronic news content is a burden for human to come out with valuable information. For mitigating this pain point, this paper proposes an automatic method to summarize Bangla news document. In this proposed approach, graph based sentence scoring feature is introduced for the first time for Bangla news document summarization. After analyzing vast amount of Bangla news document 12 sentence scoring features have been introduced for calculating score of a sentence. An improved summary generation method has also been proposed which remove the redundant information from summary. The result is evaluated using a standard summary evaluation tool called ROUGE, and found proposed method outperforms all existing methods used in Bangla news summarization.