MAKING MANAGEMENT DECISIONS OF THE ELECTRIC POWER SYSTEM USING THE PARACONSISTENCY LOGICAL MODEL OF THE EXPERT SYSTEM (PESPAL2V)

This article describes an expert system that is designed and developed for a certain and limited application of human knowledge. Equipped with an information base, it is able to make decisions based on reasonable knowledge. At the same time, the algorithms from which the computational program of the expert system consist, represent knowledge from the area they should analyze and help solve problems.

Electronic Properties of Ethylene Glycol and Styrene Glycol: DFT Calculation

In this paper we worked on a theoretical study of Ethylene glycol and styrene glycol Which is based on density functional theory, implement in computational program SIESTA with use of general gradient approximation (GGA) of Perdew, Burke and Emzerhof (PBE) scheme for an account of exchange co-relation effect to obtain density of state , projected density of state and charge density. Keywords: Density functional theory, SIESTA, Density of state .Projected density of state ,charge density .

Bin2vec: learning representations of binary executable programs for security tasks

Tackling binary program analysis problems has traditionally implied manually defining rules and heuristics, a tedious and time consuming task for human analysts. In order to improve automation and scalability, we propose an alternative direction based on distributed representations of binary programs with applicability to a number of downstream tasks. We introduce Bin2vec, a new approach leveraging Graph Convolutional Networks (GCN) along with computational program graphs in order to learn a high dimensional representation of binary executable programs. We demonstrate the versatility of this approach by using our representations to solve two semantically different binary analysis tasks – functional algorithm classification and vulnerability discovery. We compare the proposed approach to our own strong baseline as well as published results, and demonstrate improvement over state-of-the-art methods for both tasks. We evaluated Bin2vec on 49191 binaries for the functional algorithm classification task, and on 30 different CWE-IDs including at least 100 CVE entries each for the vulnerability discovery task. We set a new state-of-the-art result by reducing the classification error by 40% compared to the source-code based inst2vec approach, while working on binary code. For almost every vulnerability class in our dataset, our prediction accuracy is over 80% (and over 90% in multiple classes).

Computational program to evaluate local defects type Chalmers Test on a reflective optical surface

A computational tool is developed to measure the local deformations in optical surfaces from the interference patterns obtained by the Chalmers test principle and from the analysis of a reflective optical surface using a commercial Fizeau interferometer of the ZYGO. The tests were made on a concave spherical mirror with a radius of curvature of 60 cm and a diameter of 13 cm. To obtain the measurements of local deformations, a computational tool proposed for the localization of dark fringes is used by evaluating the maximum and minimum of the image obtained in the interference patterns. The results obtained show that the computational tool allows locating fringes within an interference pattern, allowing faster inter-fringe measurements and assigning an error on the surface in terms of wavelength.

Effect of the In-Cylinder Back Pressure on the Injection Process and Fuel Flow Characteristics in a Common-Rail Diesel Injector Using GTL Fuel

The presented paper aims to study the influence of mineral diesel fuel and synthetic Gas-To-Liquid fuel (GTL) on the injection process, fuel flow conditions, and cavitation formation in a modern common-rail injector. First, the influence on injection characteristics was studied experimentally using an injection system test bench, and numerically using the one-dimensional computational program. Afterward, the influence of fuel properties on internal fuel flow was studied numerically using a computational program. The flow inside the injector was considered as multiphase flow and was calculated through unsteady Computational Fluid Dynamics simulations using a Eulerian–Eulerian two-fluid approach. Finally, the influence of in-cylinder back pressure on the internal nozzle flow was studied at three distinctive back pressures. The obtained numerical results for injection characteristics show good agreement with the experimental ones. The results of 3D simulations indicate that differences in fuel properties influence internal fuel flow and cavitation inception. The location of cavitation formation is the same for both fuels. The cavitation formation is triggered regardless of fuel properties. The size of the cavitation area is influenced by fuel properties and also from in-cylinder back pressure. Higher values of back pressure induce smaller areas of cavitation and vice versa. Comparing the conditions at injection hole exit, diesel fuel proved slightly higher average mass flow rate and velocities, which can be attributed to differences in fluid densities and viscosities. Overall, the obtained results indicate that when considering the injection process and internal nozzle flow, GTL fuel can be used in common-rail injection systems with solenoid injectors.

Computational modelling of urban drainage network using LID alternatives in a sub-basin in the city of Maringa, Parana, Brazil

With urbanization development, inundations and urban floods become more frequent. In the city of Maringa, Parana, this type of event is often observed in some specific dense urban locations, resulted by intense rainfall. In this context, the objective of this paper is to perform a computational modelling in the urban drainage network, most specifically in the sub-basin defined by the intersection of avenues Guaiapo and Palmares, in the city of Maringa, Parana, considering the current situation and with the application of Low Impact Development (LID) compensatory techniques. In this regard, the computational program SewerGEMS® was used to develop the scenarios simulations. The results shown that the actual network is undersized (Scenario 01), and it is proposed the adoption of LID compensatory measures (Scenarios 02, 03 and 04). The computational modelling in the elaboration of the scenarios was effective and it may support the municipal urban management with the implementation of an adequate and efficient system of stormwater management.

Some Analytical Considerations Regarding the Traveling Salesman Problem Solved with Wolfram Mathematica Applications

The paper presents an introduction to the Ant Colony Optimisation (ACO) algorithm and methods for solving the Travelling Salesman Problem (TSP). Documenting, understanding and knowledge of concepts regarding the emergent behavior and intelligence swarms optimization, easily led on solving the Travelling Salesman Problem using a computational program, such as Mathematics Wolfram via Creative Demostration Projects (*.cdf) module. The proposed application runs for a different number of ants, a different number of ants, a different number of leaders (elite ants), and a different pheromone evaporation index. As a result it can be stated that the execution time of the algorithm to solve the TSP is direct and strictly proportional to the number of ants, cities and elite ants considered, the increase of the execution time increasing significantly with the increase of the variables.

The Cash-in-Advance Model—Second Step

The chapter extends the cash-in-advance model to allow for multiple periods, develops an equilibrium characterization, and shows how to write the first steady state computational program. The model is then used to quantify the costs of inflation, determine that optimal policy implies Friedman’s rule, and compare the gains from lower inflation vs. higher growth.