Digital levels significantly simplify field work with regards to automated staff reading, measurement corrections and data storage. However, these instruments are subject to a number of influences whose effects can cause errors in measurements. This especially applies to the negative influence of refraction, which is a serious limiting factor of accuracy in precise levelling. It is still necessary to rectify the effects of refraction via professional analysis of levelling conditions and then choose the best methodology of work. It is particularly important to determine the optimal line-of-sight distance, which yields quality results while keeping greater work productivity. The impact of sight distance of a Leica DNA03 digital level on the final results of levelling network was investigated and described in this article.

There is the specific situation in secondary schools regarding students' understanding of the importance of acquired knowledge which they need for the continuation of their education. Therefore, nowadays it is necessary to introduce innovative forms of knowledge acquiring such as blended learning. The intention is to build an adequate model using Mamdani Fuzzy Logic in terms of better motivation of students with higher and lower metacognitive skills for the online part of teaching. The aim of applied Mamdani Fuzzy Logic method is to determine the best ratio of number of logins on the LMS system, test results and time spent on the LMS system that would give the best results at the final testing. The achieved results show that the applied method effectively determines the best ratio of these three variables in order to achieve the best results at the final testing of different groups of students according to metacognitive skills. 

The IP-based storage systems often require bandwidth intensive access to storage devices, thus they exhibit high CPU utilization and low throughput when executed in a principally software implementation. This is especially evident for multi-Gbps networks where the impact of computational overhead is so pronounced that the current state of the art processors cannot take advantage of the capacity of the network. In this paper we propose new iSCSI Offload Engine architecture for high data rate storage networking. Based on our analysis of open source Open-iSCSI initiator, we offload the most computationally intensive and the most executed functions in a common case scenario, while other functions are implemented in a modified Open-iSCSI initiator on a general purpose processor. Our architecture overcomes the performance limitations imposed by a single processor which runs on 15x higher operating frequency than our accelerator. It exhibits very low CPU utilization of approximately 3% on the host CPU, which is 10–15x reduction compared with software implementation. The maximum transmission throughput is 7.81 Gbps, while reception throughput is 7.34 Gbps, which is 2 times speedup over software. The new architecture also shows comparable performance with Chelsio T110 ASIC-based HBA, and has more flexibility.