THE METHOD OF OBJECT MODELING IN THE DEVELOPMENT OF PATENTABLE DESIGNS OF TRACTION DRIVE MECHANISMS

Work objective is to develop a patentable design of locomotive traction drive mechanisms using the example of a suspension unit. Research methods: object modeling method, analytical methods for calculating dynamics of rolling stock. Research results and novelty: the design of the railway electric motor suspension unit, which will reduce costs in the course of maintenance and repair of a locomotive with a solid gear by increasing the reliability of the suspension unit parts, eliminating their wear, has been developed; a compensation coupling device has been devised. We will synthesize the object model of a technical system based on the identification of its typical structure by classifying technical systems. Conclusion: the application of the object modeling method together with the object model allows avoiding errors in the development of new designs of technical objects based on existing comparables and eliminates defects of the selected prototype. The use of the object modeling method makes it possible to synthesize patentable designs of the locomotive underframe mechanisms.

ОСОБЛИВОСТІ ЗАСТОСУВАННЯ МЕТОДІВ ФІЗИЧНОГО МОДЕЛЮВАННЯ ДЛЯ АНАЛІЗУ ПРОЦЕСУ ПРИЗЕМЛЕННЯ ПАРАШУТНИХ ПЛАТФОРМ НА НАДУВНІ ПОВІТРЯНІ АМОРТИЗАТОРИ

Research has been carried out aimed at developing the theoretical bases of physical modelling of landing processes of parachute platforms on inflatable air shock absorbers. At the same time, the features of the application of physical modeling methods for solving this task are considered. The conditions, landing features and operation of parachute platform devices at landing on inflatable air shock absorbers are determined. It is shown that presently parachute-depreciation systems have become widespread, in which soft tissue shells are used, filled through the inlet openings with atmospheric or air injected from gas bottles air. The operation of these devices is based on the compression of air in the shell and expiration of him through exit holes (valves). At the same time, air inflatable shells absorb the kinetic energy of the impact, controlling the release of air through exit holes.It has been established that the most effective method for studying the behavior of a dropped vehicle is physical modelling, which uses a free-flying dynamically similar model (FDSM) or stand dynamically similar model (DSM) of a dropped object as an research object. Modeling of landing processes of parachute platforms on inflatable air shock absorbers is not related to the dynamics of the flight and air flow around surfaces. Therefore, for this task, the existing developments in physical modelling of dynamics flight cannot be applied, and for the theoretical substantiation of the dynamic similarity to modeling motion, it makes sense to use the laws of gas dynamics in regard to air shock absorbers.

Pemanfaatan E-Commerce untuk Optimalisasi Penjualan dan Pemasaran Produk Shopsock Berbasis Web

Shopsock is one type of business in the field of shoe sales, so far the sale of shopsock products has been carried out by interacting with direct consumers and the marketing is not optimal. To optimize product sales and marketing, in this study an online sales website (e-commerce) was built to display information on products sold in shopsock stores and customers can easily make purchases. This website was built using the waterfall method, object modeling using UML, open source programming tools based on PHP, MySQL database and the result achieved is an e-commerce website to expand market prey for promotion and make it easier for consumers to buy shopsock products

Method of invariant assessment of quality and efficiency marine engineering and marine infrastructure facilities

В развитие Полимодельного квалиметрического метода системной оптимизации объектов морской техники рассмотрена математическая модель и методика инвариантной оценки качества объектов исследовательского проектирования и их систем. Обобщены свойства Полимодельного квалиметрического метода, сравнительные свойства алгоритмов агрегирования показателей качества и предложена методика инвариантной оценки качества и эффективности, а также системной оптимизации объектов морской техники и морской инфраструктуры как объектов исследовательского проектирования. Разработанные основные положения методики на примере объекта морской техники класса «Корабль» позволяют количественно оценивать качество, эффективность, конкурентную способность и перспективность развития в условиях лавинообразного роста сложности современных объектов морской техники, ужесточения требований к качеству процессов их создания и эксплуатации на всех этапах жизненного цикла. Это позволяет на принципиально новом уровне решать задачи концептуального, исследовательского и конструкторско-технологического обоснования эффективных и оптимальных проектных и эксплуатационных решений за счет специфики инвариантного моделирования объектов. In the development of a multi-Model qualimetric method for system optimization of marine engineering objects, a mathematical model and a method for invariant assessment of the quality of research design objects and their systems are considered. The properties of the Polymodel qualimetric method, comparative properties of algorithms for aggregating quality indicators are generalized, and a method for invariant assessment of quality and efficiency, as well as system optimization of marine engineering and marine infrastructure objects as research design objects is proposed. The developed basic provisions of the methodology on the example of a Ship-class marine equipment object allow us to quantify the quality, efficiency, competitive ability and prospects of development in the conditions of an avalanche of increasing complexity of modern marine equipment objects, stricter requirements for the quality of their creation and operation processes at all stages of the life cycle. This allows us to solve the problems of conceptual, research and design-technological justification of effective and optimal design and operational solutions at a fundamentally new level due to the specifics of invariant object modeling.

Modeling a Competence-based Industry Role Selection System for University Graduates Using Machine Learning

This paper presents a design of a system for industry role selection, representing both its structure and behavior. Knowing the right industry role that suits a graduate based on their competences on graduation has remained a critical matter for graduates when searching for jobs after graduation. Thousands of university students graduate each year and enter the market to search for jobs that are limited. Searching without prior information on the most appropriate industry role one is suitable for leads to blind search. Blind search not only puts graduates at risk of long-term unemployment and job mismatch but also overloads employers with many applications during job selection. Therefore, this paper addresses 2 objectives: 1) to model the system’s structure, and 2) to design the algorithm for the system’s behavior. Since object-oriented programming is currently the dominant programming paradigm, object modeling technique was selected to model both the system’s structure and the algorithm for the system’s behavior. To realize object modeling and represent the system’s artifacts in a highly simplified form, Unified Modeling Language (UML) was adopted as the standard modeling toolkit. More specifically, UML class diagram was used to represent the structural model of the system where the underlying objects of the model were exactly similar to those of the problem domain. Finally, use case diagram of the UML toolkit was used to represent the system’s behavior in selecting industry role for graduates. To ensure that the system improves performance of its behavior through experience in selecting industry roles for graduates, Machine Learning (ML) algorithm was designed. Two machine learning techniques, naïve Bayes and Support Vector Machines (SVM), were used as the algorithm’s criteria for selecting industry roles for graduates. Experiments to evaluate performance of the system were conducted using data collected from Software Engineering industry domain. The end product was design of an intelligent industry role selection system with relevant structure and behavior to easily work with both in the academia and industry. Findings reveal the system improves performance of its behavior in selecting industry roles for graduates much better under SVM (67%) than naïve Bayes (57%). On the same benchmark dataset, the system recorded better performance (85%) than reported performance (82%) in the benchmark system. These findings will benefit industry by getting evaluation tool for revealing graduate’s suitability for employment which they can use as prior information for decision making when filtering candidates for interview. Besides, this will provide researchers with a digital platform to study and bridge the gap between industry and academia. Lastly, this will attempt to reduce both low job satisfaction and long-term unemployment that is one of the causes of social and economic pain both in Kenya and around the world. This paper has revealed competence based industry role selection system with relevant structure and behavior can improve searching of jobs by providing a fairly accurate prior information. However, this paper recommends testing this approach with other alternative machine learning techniques as well as other alternative industry domains.