ANALYSIS OF MANAGEMENT OF PRODUCTION POTENTIAL OF MACHINE-BUILDING ENTERPRISES OF KHARKIV REGION

The purpose of the article is to study the management of production potential of machine-building enterprises in the Kharkiv region, 9 enterprises were analyzed and their production indicators were studied. The effectiveness of the production potential is characterized by production, technological, financial and innovative components. It should be noted that since the production potential is a component of the economic potential of the enterprise, the structure presented in Fig. 1 is quite conditional. If we consider the production potential from this point of view, then, for example, its innovative component is inextricably linked with the innovative potential, and the financial component – with the financial potential. Sustainable development and competitiveness of an industrial enterprise depends on the level of production potential, which is the foundation of production activity. The production potential of an industrial enterprise is a complex, dynamic and stochastic system consisting of a number of interconnected components. At the legislative level, an attempt has been made to build a single model of an integrated indicator of the financial condition of large, medium and small enterprises. According to the approved IFI Procedure for assessing the financial condition of a potential beneficiary of an investment project, the level of financial condition of the enterprise is determined depending on the value of the integrated indicator, which allows the classification of enterprises in the industry or region. At the same time, questions about the structure of innovation potential remain controversial in the scientific literature. The development of an integrated module for the assessment of production potential is the first stage of the presented methodological approach. The next step is to improve the information subsystem of monitoring the financial and economic activity of industrial enterprises, which in turn is an integral part of the IT system of enterprise management. At this stage, it is necessary to develop software that provides analysis and comprehensive assessment of production capacity. After integrating the software module with IS monitoring, we have to test the software using the collected database on the financial and economic activity of the enterprise. Comparing the results of the assessment with the assessment from the analytical reports of independent experts will allow to determine the level of adequacy of the presented model and software. Methodology. The analysis was conducted on the basis of financial statements of enterprises of the machine-building industry of Kharkiv region for the period 2018, 2019, 2020. Results of the study show that the enterprises of the machine-building industry have low indicators of production potential, so enterprises need to change the strategy in the market to improve production capacity to increase competitiveness and improve. Practical implications. Given that companies have lost traditional markets in recent years and products are not in high demand in European markets, it is necessary to develop ways to improve the management of the potential of machine-building enterprises, seek new markets and strengthen cooperation with international companies. Value/originality. The study will help the management of enterprises to more effectively manage the enterprise and improve their production capacity.

Methodology for Designing Systems Based on Tangible User Interfaces and Gamification Techniques for Blind People

Having a disability does not mean being away from major technologies present today; even people with visual impairment or blindness use different options to access technological information. Recent studies have shown that using tangible user interfaces and gamification techniques brings considerable benefits to learning and the understanding of essential topics for these people. Therefore, METUIGA methodology has been developed to facilitate digital content creation that mixes both characteristics and seeks to take advantage of the primary means of knowledge that these people have as their sense of touch, enriched with techniques that encourage them to use applications more frequently. For this reason, novelties are shown within the requirements and the design stages to implement these techniques. This work shows prototypes that have been made following METUIGA methodology to help teach geometry and mathematical lessons for blind people. In addition, a third prototype focused on children with an autism spectrum disorder demonstrates how METUIGA methodology can be applied in a variety of subjects and for a number of disabilities. Finally, an analysis of the software methodology evaluation is presented to show the initial perceptions of software developers toward METUIGA methodology, where important results were obtained in relation to the software engineering process application.

Software Methodology for Estimating the Efficiency of the Hardware Composition of Deep Packet Inspection System Using the Modernized Hooke ‒ Jeeves Method

Deep packet inspection systems on communication networks are used to identify the application generating a specific traffic flow. The issues related to modeling and design of deep packet inspection systems remain poorly understood. In this paper, a software technique for evaluating the effectiveness of the hardware composition of the servers of the deep packet inspection system is presented, using a mathematical model of such a system and software search methods. The description of the program search by the maximum element method and the Hook - Jeeves method is given. A modernization of the Hook-Jeeves method for a monotonically decreasing function is proposed. Comparison of the methods by the number of search steps is performed.

iPlus a User-Centered Methodology for Serious Games Design

Standard video games are applications whose development process often follows a traditional software methodology. Serious Games (SGs) are a tool with an immensely positive impact and great success. SGs enable learning and provide entertainment and self-empowerment, which motivates students. The development of an SG consists of complex processes requiring multi-disciplinary knowledge in multiple domains, including knowing the learning domain and adding the appropriate game mechanics to foster high intrinsic motivation and positive player experience that makes the players feel like they are having fun while learning. Otherwise, the game is viewed as boring and not as a fun and engaging activity. Nevertheless, despite their potential, the application of SGs in education has been limited in terms of pedagogy. Several authors assert that this lack is because SG standards and guidelines have not been developed. There is an imbalance between experts’ contributions to education and game design specialists for the SG development. Not all the SGs that have been developed have applied appropriate design methodologies that incorporate both the entertainment mechanics and the serious component. To ensure that an SG meets the user’s expectations, it must be designed using an appropriate method. This work aims to present iPlus, a methodology for designing SGs based on a participatory, flexible, and user-centered approach. Additionally, this paper analyses several case studies with the iPlus methodology.

Universal Differential Equations for Scientific Machine Learning

In the context of science, the well-known adage “a picture is worth a thousand words” might well be “a model is worth a thousand datasets.” Scientific models, such as Newtonian physics or biological gene regulatory networks, are human-driven simplifications of complex phenomena that serve as surrogates for the countless experiments that validated the models. Recently, machine learning has been able to overcome the inaccuracies of approximate modeling by directly learning the entire set of nonlinear interactions from data. However, without any predetermined structure from the scientific basis behind the problem, machine learning approaches are flexible but data-expensive, requiring large databases of homogeneous labeled training data. A central challenge is reconciling data that is at odds with simplified models without requiring "big data". In this work demonstrate how a mathematical object, which we denote universal differential equations (UDEs), can be utilized as a theoretical underpinning to a diverse array of problems in scientific machine learning to yield efficient algorithms and generalized approaches. The UDE model augments scientific models with machine-learnable structures for scientifically-based learning. We show how UDEs can be utilized to discover previously unknown governing equations, accurately extrapolate beyond the original data, and accelerate model simulation, all in a time and data-efficient manner. This advance is coupled with open-source software that allows for training UDEs which incorporate physical constraints, delayed interactions, implicitly-defined events, and intrinsic stochasticity in the model. Our examples show how a diverse set of computationally-difficult modeling issues across scientific disciplines, from automatically discovering biological mechanisms to accelerating the training of physics-informed neural networks and large-eddy simulations, can all be transformed into UDE training problems that are efficiently solved by a single software methodology.

Hybridized Design For Feature Optimization and Reduction of Intrusion Detection Systems Alert in a Correlation Framework

The Intrusion Detection System (IDS) produces a large number of alerts. Many large organizations deploy numerous IDSs in their network, generating an even larger quantity of these alerts, where some are real or true alerts and several others are false positives. These alerts cause very severe complications for IDS and create difficulty for the security administrators to ascertain effective attacks and to carry out curative measures. The categorization of such alerts established on their level of attack is necessary to ascertain the most severe alerts and to minimize the time required for response. An improved hybridized model was developed to assess and reduce IDS alerts using the combination of the Genetic Algorithm (GA) and Support Vector Machine (SVM) Algorithm in a correlation framework. The model is subsequently referred to as GA-SVM Alert Correlation (GASAC) model in this study. Our model was established employing the object-oriented analysis and design software methodology and implemented with Java programming language. This study will be benefitted by cooperating with networked organizations since only real alerts will be generated in a way that security procedures can be quickly implemented to protect the system from both interior and exterior attacks

Experimental Application of the Process Industry Solid Particle�s Displacement in a Vertical air Flow

In this article some experimental studies were performed in order to analyze some physical parameters specific for a solid particle during displacement in a vertical air flow. The analyzed parameters were the instantaneous average velocity value and the angular velocity value. To determine the two parameters, a laboratory stand was used for the aerodynamic separation of a mixture of solid particles and a high-speed video camera in order to be able to track the behaviour of the studied particles. At the same time, a working methodology has been designed, implying the use of multiple software, i.e. analysis, video, imagistic and date software, methodology that aims to convert a video file, where we have a 2D view, into a 3D interpretation. Following the analysis of the obtained results, we noticed that both the instantaneous average velocity value and the angular velocity value are closely linked to the sphericity of the solid particle, varying inversely proportional to it, and to the air flow velocity, which directly influences the analyzed parameters.

RANCANG BANGUN GAME TREASURE OF LABYRINTH DENGAN ALGORITMA BACKTRACKING BERBASIS ANDROID

Games are one of the entertainment media which is the choice of almost everyone to get rid of boredom or just fill in spare time, there are also games used as hobbies and moreover games are now used as electronic sports (e-sports). Currently the game has many types of games, one of which is a type of puzzle game (puzzle). One puzzle game is a maze game. The labyrinth is a puzzle that has a complex branching form and has many dead ends. At the moment there are many labyrinth type games, but rarely are labyrinth games equipped with characters, enemies and a dynamic maze that can change if the game is repeated. To create a labyrinth game that has a dynamic labyrinth arena requires a labyrinth generator or can be called a labyrinth generator by utilizing the backtracking algorithm. This algorithm is powerful enough to be used in some problem solving and also to provide artificial intelligence in the game. The software methodology used in making games is the GDLC (Game Development Life Cycle). GDLC is a game development model that adopts an iterative approach consisting of 6 development phases, starting from the innitiation, pre-production, production, testing, beta and realese phases. for the generation of the labyrinth arena using the Backtracking algorithm while for testing this game uses the UAT (User Acceptment Test). The results of this study in the form of an adventure game based on a maze puzzle that is applied to mobile android. This game is played to train players in problem solving and entertainment facilities.Keywords: Puzzle Game, GDLC (Game Development Life Cycle), Backtracking Algorithm, Android