Драгомир Господинов Добруджалиев е роден на 1 юли 1949 г. в Нова Загора. Израснал и възпитан в семейството на интелигентни, ученолюбиви и прогресивни хора, той завършва основното и средното си образование с пълно отличие и съответно с „Палаузовска награда“ и Златен медал от Министерството на народната просвета.
Месец: март 2025
годишнина
75-годишен юбилей на проф. д-р инж. Ангел Смрикаров
През 2024 г. проф. д-р Ангел Сотиров Смрикаров навърши 75 години. Той е роден на 19 август 1949 г. в Русе. През 1968 г. завършва Техникума по електротехника в гр. Русе, специалност радио и телевизия с пълно отличие и златен медал.
информатика
С. Мизанали, А. Килитчи Калайър, Интелигентни домове и взаимодействие между хора и компютри: оценка от гледна точка на сигурността
Key Words: Human-Computer Interaction; smart home systems; security; human-computer interface.
Abstract. Human-Computer Interaction (HCI) is a critical field of study that has gained increasing importance over time. Today, smart home systems are among the most common application areas of human-computer interaction. These systems offer efficiency and end-to-end connectivity to users. Moreover, IoT frameworks and other technological integrations are widespread and indispensable components of these systems. However, significant security concerns and vulnerabilities associated with these systems are also on the rise. This study examines the relationship between HCI and smart home systems, focusing on the requirements for intuitive and secure interface designs. The research highlights the need for the convergence of HCI interface designs with smart home systems, emphasizing the necessity for continuous innovation and improved security mechanisms. It also underscores that future advancements in cutting-edge technologies, such as artificial intelligence, 5G/6G, blockchain, and quantum computing, are expected to present both opportunities and challenges to the design and operation of smart home systems. In conclusion, as interactions between humans, advanced technologies, and smart systems become more frequent, the application of HCI principles in the design of smart home systems will become increasingly crucial. Ensuring that these systems are not only usable but also secure is vital, making them safe and accessible for users with low digital literacy. Integrating both technical and human-centered perspectives in the holistic development of these systems is imperative.
автоматика
Н. Делийски, Н. Тумбаркова, Д. Ангелски, П. Вичев, К. Атанасова, Изчисляване на енергийния разход за разтопяване на леда в дървесината с използване на софтуера Table Curve 2D
Key Words: Calculation of energy; wood containing ice; melting frozen water; thermal treatment; Table Curve 2D.
Abstract. A mathematical description of the thermal energy consumption Qice required to melt the ice formed in the wood by the natural freezing of both free and bound water in it, using the software package Table Curve 2D v.5.01 has been presented. This package allows for the selection of equations, which provide the best similarity between the calculated with them values of Qice during thermal treatment of wood containing ice and the respective numerical data obtained experimentally or using an adequate temperature-energy model of Qice. For the determination of Qice, the classical approach from thermodynamics was used to calculate the energy required to heat a solid body from any initial temperature to a certain final temperature. In our case, the energy Qice is represented as a sum of the energy Qice-bw required to melt the initial temperature-dependent frozen portion of the bound water in the wood, and the energy Qice-fw required to melt the ice formed by freezing all the free water in the wood. The energies Qice-bw and Qice-fw are represented as a product of the ice density with the specific heat capacities of the frozen bound and free water in the wood and the temperature ranges in which the melting of the two types of frozen water takes place. Mathematical descriptions of the specific heat capacities of frozen bound and free water in wood are also presented, taking into account the latent heat of the phase transition of water. The calculations of the energies Qice-bw, Qice-fw, and their sum Qice were made for the case of thermal treatment of frozen beech wood with an initial temperature of −1 °C, −10 °C, −20 °C, −30 °C, −40 °C and moisture content of 0.4 kg·kg-1, 0.6 kg·kg-1, and 0.8 kg·kg-1. The obtained results were processed using the Table Curve 2D software package. Three logarithmic equations of the same type were selected, which mathematically describe the dependence of Qice on the initial temperature of the frozen wood for each of the investigated values of its moisture content. It was found that there is a very small error (within the limits of only 3.5%) between the equations calculated with Table Curve and the approximate values of the Qice. The equations obtained can be used for development and automatic implementation of scientifically based energy-efficient regimes and technologies for steaming or boiling of frozen wood materials with different properties and purposes.
автоматика
М. Хаджийски, Интегриране на технологиите на изкуствения интелект в индустриалните системи за автоматизация
Key Words: Artificial Intelligence; integration; industrial automation; industrial control systems; Machine Learning; operational control; technological control.
Abstract. The newly emerging challenges of interpenetration and multifaceted integration of modern artificial intelligence technologies and leading computer systems of industrial automation are considered in the article. The relatively independent development of industrial automation and artificial intelligence has reached in the last one or two decades such a high technological level of openness, flexibility and compatibility, creating prerequisites to build integrated systems based on a holistic synthesis of a completely new type for solving tasks which until recently were considered intractable. The new conditions of competition are significantly complicated due to the extremely accelerated dynamics and depth of the various stages of industrial processes – supply chains, transportation problems, technological breakthroughs in the basic facilities and processes, malicious cyber attacks, situations resulting from global geopolitical conflicts. The main achievements that give rise to huge expectations for overcoming these and the expected future challenges are: the fundamentally new level of information treatment (Big Data), the modern achievements of computing technology (Industrial Internet of Things – IIoT, cloud technologies, computing architectures based on of graph models) and the explosive development of artificial intelligence (multidimensional and multi-aspect models, automatic prediction, decision-making and planning, revealing implicit relationships and dependencies, learning based on historical, current and simulation data, human-machine interaction of a new type ). Under the new highly complicated conditions and increased requirements, industrial automation is steadily following its trajectory of expanding its scope of action – from primarily technological control to gradually including all sides of the operational control and management (planning, production schedules, predictive maintenance of the facilities, adaptation to the goals and situations in the short and long term). The realistic approach requires strategic decisions in the development of industrial automation to be in the direction of „end-to-end automation“ by upgrading existing systems while uncompromisingly evaluating the advantages and disadvantages of the relevant artificial intelligence technologies that we have now.
