The technology of solar-powered aerial vehicles requires enormous financial support and further development. For this purpose, the computational fluid dynamic can be used. In order to carry out necessary analyses and model development in this research, ANSYS Fluent software was used. Using the first version of the AGH Solar Plane model, preliminary analysis of lift, drag and tearing off the stream were performed. Numerical experiments made it possible to verify many various profiles and final selection that the best suits the target model. Through these studies, it was also possible to analyse fluid flow at various speeds and angles of attack. This provided an insight into important aspects of vehiclesaerodynamic design, which should be taken into account when making the second model version. At this stage, the classical and laminar - Wortmann aerodynamic profiles were selected on the basis of the aerodynamic perfection criterion. Moreover, four new geometries were prepared on which the flattening of upper surfaces (for fixing solar panels) was tested. The results of the numerical analysis were validated in the aerodynamic tunnel using particle image velocimetry method. Taking into account all analyses, a number of recommendations have been prepared that will be implemented in order to create an aircraft, which meets all target requirements. Some of these hints were: testing new ways of connecting the wing to the nacelle, which would reduce the drag as well as considering the usage of winglets in order to minimize induced drag.

Real-time systems must avoid hazardous situations. To achieve this, their functionality should be investigated under time constraints. In this paper, a modeling based on Hierarchical Communicating Real-time State Machine (H- CRSM) and analysis methodology is proposed to examine statically ANSI-C code to obtain the hazardous events in the input system. A hazardous event equation is taken as input to the proposed system. The output is a list of hazardous scenarios. A path in the code showing the cause of the undesirable event is associated with each hazardous scenario. The strength of the proposed methodology is that the process of hazardous situations detection does not require running the ANSI-C program multiple times with different input values. It also focuses on analyzing the software level of the life cycle. Most of the verification tools check the system level. The system level may be bug-free but the software level may not.

In this paper, we use the alternating direction method for isogeometric finite elements to simulate implicit dynamics. Namely, we focus on a parabolic problem and use B-spline basis functions in space and an implicit marching method to fully discretize the problem. We introduce intermediate time steps and separate our differential operator into a summation of the blocks, acting along a particular coordinate axis in the intermediate time steps. We show that the resulting stiffness matrix can be represented as a multiplication of two (in 2D) or three (in 3D) multi-diagonal matrices, each one with B-spline basis functions along the particular axis of the spatial system of coordinates. As a result of this algebraic transformations, we get a system of linear equations that can be factorized in linear $O(N)$ computational cost in every time step of the implicit method. We use our method to simulate the heat transfer problem. We demonstrate theoretically and verify numerically that our implicit method is unconditionally stable for heat transfer problems (i.e., parabolic). We conclude our presentation with a discussion on the limitations of the method.

Requirements Engineering (RE) is recognized as one of the most important (yet difficult) areas of software engineering that has a significant impact on other areas of IT projects and their final outcomes. Empirical studies investigating this impact are hard to conduct, mainly due to the great effort required. It is thus difficult for both researchers and industry practitioners to make evidence-based evaluations about how decisions about RE practices translate into requirement quality and influence other project areas. We propose an idea of a lightweight approach utilizing widely-used tools to enable such an evaluation without extensive effort. This is illustrated with a pilot study where the data from six industrial projects from a single organization were analyzed and three metrics regarding the requirement quality, rework effort, and testing were used to demonstrate the impact of different RE techniques. We also discuss the factors that are important for enabling the broader adoption of the proposed approach.

Neutrosophic set (NS) is a powerful tool to deal with indeterminacy. In this paper, the neutrosophic set is applied to the image domain and a novel edge detection technique is proposed. Noise reduction of images is a challenging task in image processing. Salt and pepper noise is one kind of noise that affects a grayscale image significantly. Generally, the median filter is used to reduce salt and pepper noise; it gives optimum results while compared to other image filters. Median filter works only up to a certain level of noise intensity. Here we proposed a neighborhood-based image filter called nbd-filter, it works perfectly for gray image regardless of noise intensity. It reduces salt and pepper noise significantly at any noise level and produces a noise-free image. Further, we proposed an edge detection algorithm based on the neutrosophic set, it detectsedges efficiently for images corrupted by noise and noise-free images. Since most of the real-life images consists of indeterminate regions, neutrosophy is a perfect tool for edge detection. The main advantage of the proposed edge detector is, it is a simple and efficient technique and detect edges more efficient than conventional edge detectors.

The multi-robot task allocation problem consists of two distinct sets: a set of tasks (requiring resources) and a set of robots (offering resources); then tasks are allocated to robots; while optimizing a certain objective function, subject to some constraints: e.g. allocate the maximum number of tasks, minimize the distances travelled by robots, etc. In this paper, we propose some objective functions, and our main contribution is the introduction of energetic constraints on multi-robot task allocation problems. In addition, we propose an allocation method (based on parallel distributed guided genetic algorithms) and compare it to two state-of-the-art algorithms. Performed simulations and obtained results show the effectiveness and scalability of our solution, even with a large number of robots and tasks.

In our study, we present the results of the implementation of SHA-512 algorithm in FPGA. The distinguished element of our work is that we conducted the work using OpenCL for FPGA which is a relatively new development method for reconfigurable logic. We examine the loop unrolling; as the OpenCL performance optimisation method, and compare the efficiency of the different kernel implementation types: NDRange, Single-Work Item, and SIMD kernels. In conclusions, we compare metrics of the created FPGA accelerator to the corresponding GPGPU solutions. Also, our paper is accompanied by the source code repository to allow the reader to follow and extend our survey.

The technology that has evolved with innovations in the digital world has also caused an increase in many security problems. Day by day the methods and forms of the cyber-attacks began to become complicated, and therefore their detection became more difficult. In this work we have used the datasets which have been prepared in collaboration with Raymond Borges and Oak Ridge National Laboratories. These datasets include measurements of the Industrial Control Systems related to chewing attack behavior. These measurements include synchronized measurements and data records from Snort and relays with the simulated control panel. In this study, we developed two models using this datasets. The first is the model we call the DNN Model which was build using the latest Deep Learning algorithms. The second model was created by adding the AutoEncoder structure to the DNN Model. All of the variables used when developing our models were set parametrically. A number of variables such as activation method, number of hidden layers in the model, the number of nodes in the layers, number of iterations were analyzed to create the optimum model design. When we run our model with optimum settings, we obtained better results than related studies. The learning speed of the model has 100\% accuracy rate which is also entirely satisfactory. While the training period of the dataset containing about 4 thousand different operations lasts about 90 seconds, the developed model completes the learning process at the level of milliseconds to detect new attacks. This increases the applicability of the model in real world environment.

The aim of the article is to present the project environment for the implementation of the IT system in the district court, as well as the analysis of the entities and processes on the basis of which two models were built. The first of these models includes all identified processes to whom have been assigned responsible entities and the artefacts, arising as a result of these process. The second model is the extension of the first model with identified missing processes and entities. The analysis and identification of processes, entities and artefacts was carried out on the basis of the realized project of customization and implementation of the IT system. Customization involves the parameterization and adjusting of a standard solution to the needs of a specific recipient (Wieczorkowski, 2015), in this case to the needs of the district court. This case study is part of research in the area of project management in the common courts for the needs of doctoral dissertation. The methodology of this research is presented in the third chapter.

The aim of this research is to build an open schema model for digital sources repository in the relational database. It required us to develop a few advanced techniques. One of them was to keep and maintain a hierarchical data structure pushed into the repository. The second was to create constraints on any hierarchical level that allow enforcing data integrity and consistency. The created solution is mainly based on a JSON as a native column type, which was designed for holding open schema documents. In this paper, we present the model for any repository that uses hierarchical dynamic data. Additionally, we include a structure for normalizing input and description for data to keep all the model assumptions. We compared our solution with well-known open schema model -- Entity-Attribute-Value -- in the scope of saving data and querying about relationship and content from structure. Results have shown that we achieved improvement in both performance and disk space usage, although we extended our model with a few new features that the previous model does not include. The techniques developed in this research can be applied in every domain where hierarchical dynamic data is required, as demonstrated by the digital book repository that we have presented.