Modern Intelligent Technologies Research Articles

Intelligent Rapid Asexual Propagation Technology—A Novel Aeroponics Propagation Approach

Various rapid propagation strategies have been discovered, which has facilitated large-scale plant reproduction and cultivar development. These methods, in many plant species, are used to rapidly generate large quantities (900 mini-tubers/m2) of high-quality propagule (free from contamination) at a relatively low cost in a small space. They are also used for plant preservation. This review article aims to provide potential applications for regeneration and clonal propagation. Plant propagation using advanced agrotechnology, such as aeroponics, is becoming increasingly popular among academics and industrialists. The advancement of asexual aeroponic propagation has been achieved through advancements in monitoring and control systems using IoT and smart sensor technology. New sensor technology systems have gained substantial interest in agriculture in recent years. It is used in agriculture to precisely arrange various operations and objectives while harnessing limited resources with minimal human intervention. Modern intelligent technologies and control systems simplify sensor data collection, making it more efficient than manual data collection, which can be slow and prone to errors. Specific ambient variables like temperature, humidity, light intensity, stock solution concentrations (nutrient water), EC (electrical conductivity), pH values, CO2 content, and atomization parameters (frequency and interval) are collected more effectively through these systems. The use of intelligent technologies provides complete control over the system. When combined with IoT, it aids in boosting crop quality and yield while also lowering production costs and providing data directly to tablets and smartphones in aeroponic propagation systems. It can potentially increase the system’s productivity and usefulness compared to the older manual monitoring and operating methods.

Development of intelligent system of global bibliographic search

The paper presents scientifically grounded principles of formation and algorithms of a global bibliographic retrieval system based on modern intelligent technologies (intelligent linguistic analysis of texts and database management) and Internet search methods. Within the framework of theoretical bibliography, for the first time taking into account the specifics of modern intelligent software, a new algorithm of an integrated automated system for global bibliographic retrieval as well as search for specialized publications to publish research papers was developed. The developed methods include the formation of a normalized database of keywords based on the Universal Decimal Classification (UDC) categories and the automatic assignment of keywords from this normalized database to research papers by an intelligent system for linguistic analysis of texts. The proposed use of keywords as data labels in the form of UDC categories, covering all branches of knowledge, makes it possible to precisely label and describe research papers and scientific publications (journals, proceedings of scientific conferences) to the fullest extent possible. The search for research papers by the proposed bibliographic retrieval system as well as the search for specialized publications to publish those research papers is carried out automatically by normalized keywords assigned to research papers and scientific journals based on intelligent linguistic analysis of the content of those research papers. The study makes a social contribution and shows how it is important to create and utilize best practices, processes and strategies of bibliographic retrieval, which are essential in the development of science in modern society. Besides, in social terms, the search for bibliographic information is one of the methods to solve the problem of finding a relation between personal and public knowledge. The implementation of the study results in accordance with the presented algorithms consists in designing a special global public Internet search resource.

Development of intelligent technology elements to establish optimal harvest dates for grain crops

The outstripping pace of agro-industrial complex development is largely determined by the level of agricultural production organization. The effectiveness of crop cultivation depends both on external factors: nature of soils, climatic conditions, etc., and on the skillful organization of agrotechnical measures, timely implementation of planned sowing cycles, cultivation and harvesting of crop production. The development of intelligent technologies can optimize the use of resources and management processes in the field of agriculture, as well as improve the quality of finished products. In particular, using the capabilities of artificial intelligence, it is possible to process large amounts of data on soil composition, fertility, humidity, and other soil parameters; predict weather and climate, forecast and plan sowings of certain crops. With the help of modern intelligent technologies, it is possible to monitor the condition of plants, identify diseases and pests, control growth and determine the best time for sowing, various types of plant treatment and time for harvesting. Definitely, these are just some areas where intelligent technologies in agriculture that can be used. With the development of technology and improved data availability, the possibilities of using artificial intelligence in all the areas mentioned will only grow.

Automatic sign language translation system using neural network technologies and 3D animation

Implementation of automatic sign language translation software in the process of social inclusion of people with hearing impairment is an important task. Social inclusion for people with hearing disabilities is an acute problem that must be solved in the context of the development of IT technologies and legislative initiatives that ensure the rights of people with disabilities and their equal opportunities. This substantiates the relevance of the research of assistive technologies, in the context of software tools, such as the process of social inclusion of people with severe hearing impairment in society. The subject of research is methods of automated sign language translation using intelligent technologies. The purpose of the work is the development and research of sign language automation methods to improve the quality of life of people with hearing impairments in accordance with the "Goals of Sustainable Development of Ukraine" (in the "Reduction of Inequality" part). The main tasks of the research are the development and testing of methods of converting sign language into text, converting text into sign language, as well as automating translation from one sign language to another sign language using modern intelligent technologies. Neural network modeling and 3D animation methods were used to solve these problems. The following results were obtained in the work: the main problems and tasks of social inclusion for people with hearing impairments were identified; a comparative analysis of modern methods and software platforms of automatic sign language translation was carried out; a system combining the SL-to-Text method is proposed and investigated; the Text-to-SL method using 3D animation to generate sign language concepts; the method of generating a 3D-animated gesture from video recordings; method of implementing the Sign Language1 to Sign Language2 technology. For gesture recognition, a convolutional neural network model is used, which is trained using imported and system-generated datasets of video gestures. The trained model has a high recognition accuracy (98.52%). The creation of a 3D model for displaying the gesture on the screen and its processing took place in the Unity 3D environment. The structure of the project, executive and auxiliary files used to build 3D animation for the generation of sign language concepts includes: event handler files; display results according to which they carry information about the position of the tracked points of the body; files that store the characteristics of materials that have been added to certain body mapping points. Conclusions: the proposed methods of automated translation have practical significance, which is confirmed by the demo versions of the software applications "Sign Language to Text" and "Text to Sign Language". A promising direction for continuing research on the topic of the work is the improvement of SL1-to-SL2 methods, the creation of open datasets of video gestures, the joining of scientists and developers to fill dictionaries with concepts of various sign languages.

Devising an approach to safety management of vessel control through the identification of navigator’s state

The object of this study is the processes of automated management of maritime safety by analyzing the manifestations of the human factor of sea navigators. The task solved is justified by the need for formal and logical analysis and intelligent identification of mental motivational states (MMS) of marine navigators whose actions can cause dangerous situations during the control of the ship’s movement. High accident rates due to the fault of the navigators, in the absence of automated means of monitoring their condition, cause a contradiction between the existing means of safety control in controlling the movement of the vessel and the modern requirements of navigation, which needs to be resolved. A safety management approach was devised that takes into account the specificity of navigational tasks and the p-adic classification of dangerous MMS for navigators. This has made it possible to create three security modes that are activated depending on the detected state of the navigator’s MMS. Features of the results are the combination of analysis by means of p-adic systems and intelligent methods of data processing. As a result, sufficient identification accuracy was obtained for more than 75 % of MMS through neural network training. Experimental data collected during the navigation watch, as well as on the Navi Trainer 5000 navigation simulator (Wärtsilä Corporation, Finland), became the basis for simulation by means of neural networks. In turn, the training of neural networks made it possible to obtain sufficient identification accuracy by performing up to 3000 iterations. Overall, the learning rate of the neural network was 0.98, which indicates a high level of identification. From a practical point of view, the results could be used for the automated management of shipping safety, as well as for evaluating the level of adaptation of the navigator to dynamically changing conditions. The proposed approach provides opportunities for the application of modern intelligent technologies in the field of maritime transport safety, namely artificial neural network tools that determine notification modes or activation of automatic ship traffic control modules. The specified contradiction requires the design of specialized systems for automated safety management of ship traffic control based on the identified states of navigators

STRENGTH AND DURABILITY OF CONCRETES WITH A SUPER ABSORBENT POLYMER ADDITIVE

The article presents an analysis of the results of experimental studies of the effect of different types of a super absorbent polymer additive on the strength of different types of concrete. The study is aimed at the effectiveness of a new type of super absorbent additive in concrete structures. In the course of full-scale experiments, it was possible to identify the optimum dosage of SAP for fine-grained and heavy concretes. In addition, the results showed that the strength of concrete remains unchanged if the dosage of super absorbent polymer additive (SAP) is 0.5% of the weight of cement or less. The possibility of modern intelligent technologies (artificial neural networks) to predict the properties of concrete mixture and hardened concrete at given values of input parameters (SAP dosage and W/C), influence on concrete characteristics (slump of the cone, bending strength, compressive strength) has also been shown.

Research on Machine Vision Technology and its Application in Mechanical Manufacturing Automation

Machine vision technology was also an important part in the modern intelligent technology, as its cooperation with mechanical engineering automation could achieve technical complementation, promote the effective completion of mechanical automation production goals, and bring significant positive effects. In this paper, the machine vision technology was introduced, and the specific applications of machine vision technology in measurement, mechanical positioning, welding robot as well as other aspects of the mechanical manufacturing automation were analyzed. Meanwhile, the applications of machine vision technology in optical projection technology and agricultural production were listed. All of these not only proved that machine vision technology was an important basis for the optimization and development of mechanical manufacturing technology; but also provided some references for the integrated application of machine vision technology in mechanical manufacturing automation.

Интеллектуальные функции управления в микропроцессорных системах централизации

Trends in the development of computer-based interlocking systems are considered. The main emphasis when creating them is on achieving safety indicators no worse than those of relay analogues. The subsequent steps of improving the systems determined the directions of expansion of information support and automation of management. The main advantage of computer systems was the software implementation of a number of traditional functions that required the installation of additional relay equipment. The use of digital joints between the components of the system makes it possible to design a distributed structure of the computer-based interlocking systems on the basis of standard equipment, ensuring the rational use of computing power. Modern intelligent technologies as part of the tasks solved in the computer-based interlocking systems provide not only the choice of the best technological solutions for the organization of the station, but also allow you to exclude incorrect actions of personnel, free them from performing routine operations.

Advanced Application of Digital Technologies for Rehabilitation and Remote Monitoring of Patients with Post-Covid Syndrom: a Review

AIM. To describe modern technologies for telerehabilitation and remote monitoring of the condition of patients who have undergone a new coronavirus infection COVID-19, and to show the experience of the National Medical Research Center for Rehabilitation and Balneology of the in the clinical testing and development of these technologies. MATERIAL AND METHODS. A consistent analysis of 39 modern sources of scientific literature (including systematic reviews and original researches), selected by the keywords of this article and including the most up-to-date publications in rating peer-reviewed journals, allows us to conclude the following. The use of digital methods of rehabilitation and diagnostics in institutions of restorative medicine in patients who have had a new coronavirus infection can reduce the risks of undesirable outcomes and the burden on medical personnel, reduce the severity of manifestations of post-COVID-19 syndrome and improve the quality of life of patients. RESULTS AND DISCUSSIONS. The article describes the prospects for the use of modern intelligent technologies (virtual reality, biofeedback mechanotherapy and remote analysis of the cardiovascular system, motor activity and psychoemotional sphere) in the treatment and rehabilitation programs of patients who have suffered a new coronavirus infection COVID-19. The clinical aspects of the new coronavirus infection that determine the use of digital technologies and remote monitoring in the medical rehabilitation of patients with postcovid syndrome are presented. The technologies of virtual reality, biofeedback mechanotherapy and remote monitoring developed for the rehabilitation of patients with postcovid syndrome at the National Medical Research Center for Rehabilitation and Balneology are described in detail, data on their effectiveness, as well as limitations and difficulties possible with the introduction of digital methods of rehabilitation and telemedicine methods are given. The analysis of psychological factors of distress caused by a new coronavirus infection and approaches to their remote telemonitoring were carried out. CONCLUSION. The effectiveness of new digital rehabilitation methods that have recently appeared in clinical practice allows us to conclude that the use of modern intelligent technologies is promising. Among them, it should be noted such technologies as virtual reality, mechanotherapy with biofeedback and remote analysis of the performance of the cardiovascular system, motor activity and psycho-emotional sphere in the treatment and rehabilitation programs of patients with post-ovoid syndrome.

Метод автоматического распознавания девиантного поведения людей на основе интеграции технологий компьютерного зрения и управления знаниями для поддержки принятия решений операторами систем видеомониторинга

Ensuring safety of people in the urban environment is an important area for improving the quality of people’s lives, and the development of modern intelligent technologies creates new opportunities to achieve this goal. The use of modern intelligent technologies can realize the potential of video surveillance systems, making possible the automatic recognition of dangerous situations in real time in order to take timely measures to handle them and provide aid to victims. Often, a dangerous situation is caused by deviant behavior of people – robbery, fight, vandalism, etc. But the existing works focused on recognizing deviant behavior are only focused on recognizing short-term distinguishing features, such as punches, falls or weapons in the hands of a person. At the same time, such features may often be absent, for instance, when a passerby is robbed but no fighting occurs, which is why the task of recognizing complex long-term scenes of deviant behavior remains unresolved. This paper proposes a method for automatic recognition of long-term human deviant behavior scenes, characterized by the integration of knowledge management and computer vision technologies for detecting and segmenting objects, estimating the three-dimensional human skeleton, tracking objects in video, estimating the ground plane normal to calculate the camera distance, and classification of short-term actions of people using three-dimensional skeleton. This method can be used in the development of a decision support system by operators of video monitoring systems used to detect and handle deviant behavior of people in real time in order to prevent escalation, provide timely aid to victims and detain suspects.

Scientific and technological creative stage design using artificial intelligence

To combine traditional Chinese opera with modern intelligent technology, we use Artificial Intelligence (AI) technology to conduct innovative research on traditional stage design. In this paper, we mainly focused on the production of scientific and technological equipment for stage design, the cooperation between intelligent technology and opera culture creation, and the stage design effect and the overall stage effect after the introduction of AI technology. We elaborate on the background of AI in traditional opera art creation space and associate it with the internet collaborative creation from multiple angles through the survey as satisfaction, staff salary difference, calculation comparison, etc. The performance analysis study reveals that combining traditional Chinese opera with AI resulted in significant performance efficiency compared to conventional techniques.

Implications of Artificial Intelligence Technology for the External Communication of Chinese Ethnic Cultures

At present, artificial intelligence technology is experiencing rapid development, and artificial intelligence has a significant impact on human production and lifestyle, as well as the political and cultural aspects of society. In recent years, the rapid development of artificial intelligence, in the context of this era of development, for the national cultural communication, how to faster and better adapt to the general trend of the times, and constantly interchange and improve become an important issue. As an indispensable part of the world’s civilization, Chinese ethnic cultures cannot only focus on their domestic inheritance but also should establish an external spreading pattern, thus promoting their own development as well as the diversity of the world’s cultures. This article discusses the implication of AI technology for the promotion of Chinese ethnic cultures’ external communication. AI technology can be used in text translation, data mining, communication channel analysis, etc. It is more efficient and accurate than experienced journalists and editors in collecting big data to develop selected topics and research, judge the direction of ethnic culture communication, and discover the content that users are interested in. At the same time, the instrumental and auxiliary roles of AI translation can be used to improve the construction of ethnic culture corpus. Through the analysis of the data from the survey and experiment, it is found that the media of ethnic culture communication has changed dramatically since 2016. In 2016, the highest proportion of television channels was 70%, but in 2021, the proportion of television channels dropped to 23%, and Internet and book communication have become the “main force,” of which the proportion of Internet is 59% and the proportion of book channels is 48%, and the popularity and growth speed of the mass media ranked first. The modern intelligent technology can be used to spread Chinese ethnic cultures more widely and effectively. It has a far-reaching influence in that, it can promote the inheritance and innovation of Chinese ethnic cultures, and to improve ethnic groups’ confidence in their own ethnic cultures.

Research and Discussion on Machine Cleaning Method on Glass Wall Curtain

With the rapid development of science and technology and the cross penetration and integration of various disciplines, the glass curtain wall cleaning robot has also developed rapidly, becoming a high-tech industry in the field of service robots and a key research topic in recent years and the future. This paper summarizes the types of glass curtain wall cleaning robots and the research status of the applied technology from the aspects of adsorption mode, moving mechanism, cleaning mechanism and modern intelligent technology. At present, there is still a certain gap between the glass curtain wall cleaning robot and the goal that people are satisfied with. Finally, some suggestions are put forward for the future development trend of glass curtain wall cleaning robot.

Metamorphosis of Learning Ecosystems in Response to The Fourth Industrial Revolution's (4IR)

This review provides a comprehensive overview of the Fourth Industrial Revolution (4IR) and its educational impact. It focuses on the accelerated pace of technological advancements and the urgent need to understand how these changes affect educational systems. The research, which includes empirical studies, theoretical frameworks, and policy literature, employs a thematic analysis to identify key trends and themes using secondary data like books, research findings, and scientific journals related to 4IR. Key findings highlight the increasing demands for new skills in the workforce, ethical considerations, and the necessity for an interdisciplinary approach in education. The study underscores the transformation of education in the wake of 4IR's influence, particularly in automation and artificial intelligence (AI). It emphasizes the importance of adapting educational paradigms to address the challenges and opportunities presented by these technological advancements. The study's major implication is the need for a fundamental shift in learning ecosystems to align with the transformative power of 4IR. This involves adapting to significant changes in the educational landscape, which are necessary to facilitate user ease. Integrating modern intelligent technologies has fundamentally altered production and global supply networks, leading to increased automation, enhanced communication, and smart machines. This transformation underscores the need for educational systems to evolve and prepare for these ongoing changes.

Intelligent technologies in information retrieval systems

This paper considers the use of modern intelligent technologies in information retrieval systems. A general scheme for the implementation of Internet search engines is presented. The existing and prospective approaches to the intellectualization of individual components of this scheme are presented. An approach to the creation of a system of intelligent agents for information collection is presented. These agents are combined into teams and exchange the results of their work with each other. They form a reliable basis for the information base of search engines, ensure uninterrupted operation of the system in case of failure of individual agents. Methods for the formation of semantic networks corresponding to the texts of individual documents are also considered. These networks are considered as search patterns of documents for information retrieval and detection of duplicates or similar documents. Machine learning methods are used to conduct sentiment analysis. The paper describes an approach that made it possible to make the transition from the use of a naive Bayesian model to a modern machine learning system. The issues of cluster analysis and visualization of search results are also considered.

Overview of Smart Aquaculture System: Focusing on Applications of Machine Learning and Computer Vision

Smart aquaculture is nowadays one of the sustainable development trends for the aquaculture industry in intelligence and automation. Modern intelligent technologies have brought huge benefits to many fields including aquaculture to reduce labor, enhance aquaculture production, and be friendly to the environment. Machine learning is a subdivision of artificial intelligence (AI) by using trained algorithm models to recognize and learn traits from the data it watches. To date, there are several studies about applications of machine learning for smart aquaculture including measuring size, weight, grading, disease detection, and species classification. This review provides and overview of the development of smart aquaculture and intelligent technology. We summarized and collected 100 articles about machine learning in smart aquaculture from nearly 10 years about the methodology, results as well as the recent technology that should be used for development of smart aquaculture. We hope that this review will give readers interested in this field useful information.

INFLUENCING FACTORS OF COLLEGE STUDENTS’ PHYSICAL HEALTH UNDER THE INTERVENTION OF FOOTBALL

ABSTRACT The current football can effectively exercise the body of college students and improve their physical health. How to use modern intelligent technology to perform quantitative research on the influencing factors of football on college students’ physical health is the current development trend. Based on this, this paper studies the influencing factors of college students’ physical health under the intervention of football. First of all, this paper puts forward an analysis model of college students’ physical health based on the sarsa algorithm. The autocorrelation function is used to simulate and process the students’ physical information. Through the maximum value of the autocorrelation function curve in the detection process, the detection signal is restored, then the error of the sarsa algorithm is analyzed. Secondly, this paper expounds the influence factors of sarsa algorithm on students’ physical health in football. Fuzzy evaluation method and analytic hierarchy process are used in the evaluation. Aiming at the shortcomings of AHP, the improved sarsa algorithm is used for comprehensive analysis, and an adaptive simulation evaluation system is established. Finally, the effectiveness of the sarsa algorithm in this system is verified by many football experiments.

Neural network model of decision making in electric power facilities under conditions of uncertainty

The article is devoted to the issue of creating a mathematical model of the problem of making management decisions in electric power facilities based on modern intelligent technologies, which makes it possible to take into account the influence of various factors on the operating modes of the power system. A systematic approach to describing processes in the mathematical language of the theory of fuzzy sets is proposed. To solve the problem of controlling the operating modes of the power system, a neurofuzzy network has been developed that combines the algorithms of Takagi-Sugeno fuzzy inference, as well as a recurrent neural network. An adaptive learning algorithm based on the Frechet method is proposed for training a neural network. The analysis of the efficiency of the fuzzy control model under the conditions of various modes of functioning of the local power system is carried out.

Application Electrical Engineering Training and Intelligent Technology of Electrical and Electronic Technology under Artificial Intelligence Technology

With the development of the times and the improvement of modern industrial technology, computer technology has been greatly developed, so a new concept has been put forward, that is, artificial intelligence. And the composition of modern life is mainly electricity, so in the current era, electronic technology has been rapidly developed. But the original electrical and electronic technology can no longer match today's intelligent technology, but electronic technology is the basis of the development of modern intelligent technology. Therefore, the purpose of this paper is to use artificial intelligence technology to study the application of electrical engineering training and intelligent technology of electrical and electronic technology. After consulting the history of electrical engineering and the development, current situation and future development direction of electrical and electronic technology, this paper reviews the algorithms constructed by artificial intelligence and the basic operation of intelligent things. The improved adaptive parameter DBSCAN clustering algorithm is used to train electrical engineering and to make reference for the intelligence of electrical and electronic technology. The experimental results show that a good algorithm can speed up the training degree of electrical engineering and speed up the intelligent progress of electrical and electronic technology.

Аналіз сучасного стану та перспектив коригування енергетичного балансу підприємств гірничодобувної галузі

There has been carried out the analysis of the current state of the energy balance of mining enterprises and the sequence of further introduction of sources of distributed generation of electricity and the priority directions of correction of energy balance of mining enterprises energy sources have been offered. The structure of energy consumption of the mining industry of Ukraine is analyzed in detail to determine the share of electricity consumed in the industry relative to the total amount of energy consumed. Paying attention to the existing trends of decarbonization of world energy, ie the gradual abandonment of traditional energy sources (fossil hydrocarbons: oil, coal, natural gas, peat and others) and the increasingly active transition to renewable sources, and the introduction of modern intelligent technologies in electricity systems industrial enterprises, including enterprises of the mining industry, the energy balance of these enterprises has the potential to change both in the percentage of consumed types of fuel and energy resources, and in quantitative terms, given the increase in its own generation. It is recommended to take hydropower, wind and solar energy as one of the promising areas for the correction of the energy balance of mining enterprises.