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Large-scale automated systems such as manufacturing systems, transportation systems, the Smart Grid and many others are continuously becoming larger, more distributed, more complex, and more intelligent. There is a growing expectation that their software controller will make real-time intelligent decisions, at all levels of the control hierarchy that make up the enterprise. The need is changing for distributed intelligent controllers that are scalable to arbitrarily large systems. In this paper, we first present the model explosion problem. This problem arises when every controller in the control hierarchy is to have a unique simulation model of its unique control domain to use in its decision-making process. That is, the modeling effort needed to provide intelligence to all controllers in the control hierarchy grows exponentially with the number of controllers in the hierarchy using current modeling technology. Since each controller is in a unique location within the control hierarchy, each will need to have its simulation model custom made for its unique control domain, leading to the scalability issue that we refer to as the model explosion problem. Next, a new modeling paradigm that solves the scalability issue resulting from the model explosion problem is presented, where the simulation models are automatically generated by recycling the models used for control. If the controller models are created using the presented modeling paradigm, then these same models can be used for simulation with no modification or the need to understand the control logic. Furthermore, gathering the state from the physical system being controlled to initialize the simulation models in a real-time control application becomes a trivial operation of simply coping data from one software model to its identical copy, without the need to interpret the meaning of the data. Finally, an example of a hierarchical controller to control a small physical model of a manufacturing plant is presented. We show how we automatically generated all the simulation models in the control hierarchy without any modification and with minimal effort, and used them to make intelligent decisions in real time.

Abstract The Indian economy is greatly influenced by the Banana Industry, necessitating advancements in agricultural farming. Recent research emphasizes the imperative nature of addressing diseases that impact Banana Plants, with a particular focus on early detection to safeguard production. The urgency of early identification is underscored by the fact that diseases predominantly affect banana plant leaves. Automated systems that integrate machine learning and deep learning algorithms have proven to be effective in predicting diseases. This manuscript examines the prediction and detection of diseases in banana leaves, exploring various diseases, machine learning algorithms, and methodologies. The study makes a contribution by proposing two approaches for improved performance and suggesting future research directions. In summary, the objective is to advance understanding and stimulate progress in the prediction and detection of diseases in banana leaves. The need for enhanced disease identification processes is highlighted by the results of the survey. Existing models face a challenge due to their lack of rotation and scale invariance. While algorithms such as random forest and decision trees are less affected, initially convolutional neural networks (CNNs) is considered for disease prediction. Though the Convolutional Neural Network models demonstrated impressive accuracy in many research but it lacks in invariance to scale and rotation. Moreover, it is observed that due its inherent design it cannot be combined with feature extraction methods to identify the banana leaf diseases. Due to this reason two alternative models that combine ANN with scale-invariant Feature transform (SIFT) model or histogram of oriented gradients (HOG) combined with local binary patterns (LBP) model are suggested. The first model ANN with SIFT identify the disease by using the activation functions to process the features extracted by the SIFT by distinguishing the complex patterns. The second integrate the combined features of HOG and LBP to identify the disease thus by representing the local pattern and gradients in an image. This paves a way for the ANN to learn and identify the banana leaf disease. Moving forward, exploring datasets in video formats for disease detection in banana leaves through tailored machine learning algorithms presents a promising avenue for research.

This paper presents a novel application of Support Vector Machines (SVM) in developing automated systems to detect hate speech on social media platforms, addressing a critical need for scalable solutions to enhance online safety and societal cohesion. By leveraging SVM's proven efficacy in managing high-dimensional data and optimizing the balance between precision and recall, the study offers a comprehensive methodology that includes data collection, preprocessing, model training, deployment, and evaluation. The results demonstrate robust average performance across key metrics, affirming the model's reliability in accurately identifying hate speech while minimizing false positives. This research advances the field by showcasing the practical and theoretical contributions of SVM in automated hate speech detection, highlighting its potential to significantly improve content moderation practices. The findings underscore the necessity for ongoing refinement of detection systems and collaborative efforts among researchers, technology firms, and policymakers to create more inclusive online environments that promote respectful discourse and community well-being.

The evolving landscape of modern medicine underscores the growing importance of automating diagnostic processes. This advancement is not merely a convenience but a necessity to harness the full potential of technological progress, aiming to elevate research and clinical outcomes to new heights. Among the innovative strides in this field, the development of diagnostic systems based on morphological classification algorithms stands out. Such systems, rooted in comprehensive rule bases for differential diagnosis, promise to revolutionize the way we approach complex medical conditions. This paper introduces a cutting-edge system that epitomizes this evolution. Designed to harness the power of data analysis, it paves the way for groundbreaking research opportunities. At the heart of this system is a sophisticated set of rules derived from a morphological classification algorithm. This foundation enables the system to perform automated diagnoses of a wide array of clinical and hematological syndromes with unprecedented accuracy. A notable application of this technology is its ability to diagnose anemia by analyzing six distinct blood parameters and further categorize the anemia type based on biochemical criteria. The implications of such diagnostic capabilities are profound. By enabling the systematic collection and analysis of statistical data, the system facilitates in-depth research into the prevalence of diseases across different demographic groups. It aids in identifying disease patterns and supports preventive medicine efforts, potentially shifting the paradigm from treatment to prevention. This study not only highlights the system's capacity for enhancing diagnostic precision but also emphasizes its role as a catalyst for medical research and the improvement of healthcare delivery. The integration of such technologies into the medical field promises to enhance the quality of care, streamline diagnostic processes, and open new avenues for medical research, ultimately contributing to the advancement of global health standards.

The article highlights the issue of forming and managing customer loyalty in the service sector by using digital tools. The importance of customer loyalty as one of the most powerful components of an enterprise’s intellectual capital is emphasized. The types of loyalty are characterized according to the criteria of attitude to the brand (positive/negative) and the frequency of repeated transactions (absolute, hidden, false, zero). Loyalty indicators and how to calculate them are covered: customer retention rate, customer long-term value, Net Promoter Score, customer satisfaction surveys, customer effort evaluation, cause and effect questions, repeated purchases and referrals, engagement. It was noted that among the various types of loyalty (bonus program, fixed discount, temporary discount, multi-level discount program, product as a gift, partner loyalty program, paid loyalty program) the non-commercial program deserves the most attention, because in the long term it forms and testifies to absolute customer loyalty. The main types of loyalty management in the context of digitalization include transactional, social-network, related to the influence on engagement, emotions, consumer behavior, and intentions to recommend a service. It is emphasized that automated systems, such as software for managing business processes and online services for booking procedures, are becoming an integral part of modern beauty salons and offer a wide range of possibilities: online booking for services through a website or mobile application, reminders about visits by messages or e-mail; a calendar of appointments for services with the possibility of synchronization with personal calendars of beauty masters; automatic control of consumables balances, formation of supply orders, cash book management, income and expense accounting, profitability analysis; newsletters about promotions and special offers, maintenance of pages in social networks; storage of information about customers, their preferences, history of visits through the CRM system. The positive consequences of using automation in beauty salons include increasing efficiency and productivity, improving customer service, increasing profitability, expanding marketing and advertising opportunities, improving ratings and reviews, but among the negative ones, we single out dependence on technology, loss of personal contact, and threats to data privacy. A developed set of advertising events with seasonal specialization using online tools (conducting master classes and virtual consultations, seasonal loyalty programs, charity initiatives, promotions for special dates) is presented.

Wei-Yao Wang,1,2 Yi-Hsin Chen,3– 5 Yu-Lin Lee,1,2 Chen-Feng Chiu,6 Shih-Ming Tsao1,2 1School of Medicine, Chung Shan Medical University, Taichung, Taiwan; 2Department of Internal Medicine, Chung Shan Medical University Hospital, Taichung, Taiwan; 3Department of Nephrology, Taichung Tzu Chi Hospital, Taichung, Taiwan; 4School of Medicine, Tzu Chi University, Hualien, Taiwan; 5Department of Artificial Intelligence and Data Science, National Chung Hsing University, Taichung, Taiwan; 6Department of Internal Medicine, Feng Yuan Hospital, Ministry of Health and Welfare, Taichung, TaiwanCorrespondence: Shih-Ming Tsao, Department of Internal Medicine, Chung Shan Medical University Hospital, &num; 110, Section 1, Jianguo North Road, Taichung City, 40201, Taiwan, Tel +886 4 24739595 ext.34718, Fax +886-4-23248172, Email tsmhwy@ms24.hinet.netBackground: Determining oxacillin susceptibility using reference methods and automated systems is crucial for treating invasive infections caused by Staphylococcus aureus. This study compares the oxacillin susceptibility results from the two automated systems with agar dilution and correlates them with genotypes of invasive S. aureus.Methods: Non-duplicate S. aureus invasive isolates were collected over an 11-year period. The oxacillin susceptibility was determined with Phoenix 100 (Jan 2011 to Aug 2018) or Vitek 2 (Sep 2018 to Dec 2021), and susceptibility for oxacillin and cefoxitin was determined with agar dilution. Methicillin-resistant S. aureus (MRSA) was confirmed with mecA existence, and the genotype was determined using SCCmec. The association between genotype and antibiotic susceptibility using two automated systems and agar dilution was evaluated.Results: A total of 842 invasive S. aureus, including 443 mecA+ MRSA and 399 mecA- MSSA, were collected. The susceptibility rates of oxacillin determined by two automated systems and agar dilution were 68.8% (76.8% for Phoenix 100 and 57.6% for Vitek 2) and 54.0%, respectively. When compared with the oxacillin susceptibility using agar dilution, the categorical agreement for Phoenix 100 and Vitek 2 were 0.46% and 0.88%, respectively (p < 0.001). One hundred and forty-three isolates were misinterpreted as oxacillin-susceptible S. aureus (OSSA) using automated systems while comparing with agar dilution, among which molecularly community-associated MRSA (CA-MRSA) outnumbered healthcare-associated MRSA (HA-MRSA) (99 vs 34, p < 0.001). There were 70 mecA+ OSSA (OS-MRSA) using agar dilution, among which 42 harbored SCCmec types were predominantly categorized as CA-MRSA (38, p < 0.001).Conclusion: The categorical agreement of Vitek 2 in determining oxacillin susceptibility and predicting mecA existence is comparable with agar dilution, whereas Phoenix 100 is not. Most of those ORSA determined by agar dilution but misinterpreted as OSSA by automated systems and OS-MRSA are categorized as CA-MRSA.Keywords: oxacillin susceptibility, automated systems, agar dilution, SCCmec, CA-MRSA

Abstract In the era of automated and digitalized information, advanced computer applications deal with a major part of the data that comprises audio-related information. Advancements in technology have ushered in a new era where cutting-edge devices can deliver comprehensive insights into audio content, leveraging sophisticated algorithms such such as Mel Frequency Cepstral Coefficients (MFCCs) and Short-Time Fourier Transform (STFT) to extract and provide pertinent information. Our study helps in not only efficient audio file management and audio file retrievals but also plays a vital role in security, the robotics industry, and investigations. Beyond its industrial applications, our model exhibits remarkable versatility in the corporate sector, particularly in tasks like siren sound detection and more. Embracing this capability holds the promise of catalyzing the development of advanced automated systems, paving the way for increased efficiency and safety across various corporate domains. The primary aim of our experiment is to focus on creating highly efficient audio classification models that can be seamlessly automated and deployed within the industrial sector, addressing critical needs for enhanced productivity and performance. Despite the dynamic nature of environmental sounds and the presence of noises, our presented audio classification model comes out to be efficient and accurate. The novelty of our research work reclines to compare two different audio datasets having similar characteristics and revolves around classifying the audio signals into several categories using various machine learning techniques and extracting MFCCs and STFTs features from the audio signals. We have also tested the results after and before the noise removal for analyzing the effect of the noise on the results including the precision, recall, specificity, and F1-score. Our experiment shows that the ANN model outperforms the other six audio models with the accuracy of 91.41% and 91.27% on respective datasets.

Background: This review addresses the emerging field of automated packing cells, which lies at the intersection of robotics and packing problems. Integrating these two fields is critical for optimizing logistics and e-commerce operations. The current literature focuses on packing problems or specific robotic applications without addressing their integration. Methods: To bridge this gap, we conducted a comprehensive review of 46 relevant studies, analyzing various dimensions, including the components of robotic packing cells, the types of packing problems, the solution approaches, and performance comparisons. Results: Our review reveals a significant trend towards addressing online packing problems, which reflects the dynamic nature of logistics operations where item information is often incomplete. We also identify several research gaps, such as the need for standardized terminologies, comprehensive methodologies, and the consideration of real-world constraints in robotic algorithms. Conclusions: This review uniquely integrates insights from robotics and packing problems, providing a structured framework for future research. It highlights the importance of considering practical robotic constraints. It proposes a research structure that enhances the reproducibility and comparability of results in real-world scenarios. By doing so, we aim to guide future research efforts and facilitate the development of more robust and practical automated packing systems.

Objective. Development of automated network attack detection systems capable of adapting to the ever-changing nature of network attacks and new types of threats. Such systems should be based on machine learning algorithms and models that are able to identify complex dependencies between data in the learning process.Method. To train the models, a sample with signs of normal and abnormal traffic was prepared, and it was thinned and balanced as a result of preliminary statistical analysis. Five machine learning algorithms were selected and tested, both on a training set of features and on a real test set obtained experimentally. Based on the results of the experiments, a random forest classifier was selected, which showed the best results.Result. A model for detecting network intrusions has been developed, which showed a detection accuracy of 0.99 on real traffic.Conclusion. It is shown that a machine learning-based network intrusion detection system can solve the problem of flexible protection that could adapt to the ever-changing nature of network attacks, since one of the most important advantages of machine learning in detecting network intrusions is the ability to learn the signs of attacks and identify cases that are uncharacteristic of those that were observed earlier.

The development of information technology has contributed to the rapid process of informatization of all spheres of modern society, including library and information activities – the methods of collecting information, its visual display and providing access to it have changed; the processes of acquisition, processing of documents, preservation of collections have been transformed. The forms of information and library services have become different. The process of informatization has brought the activity of the world’s libraries to a higher level, opened up qualitatively new possibilities of performing technological operations, working via mobile devices, providing access to full-text resources in a remote mode, etc. Naturally, all these changes have also affected libraries in the Republic of Uzbekistan. Since the end of the 1990s, there began the active process of introducing information and communication technologies and automation of libraries in the republic. The work to improve the activities of the library and information institutions of the republic is still going on. The article aims to evaluate the state and degree of development of the informatization process in the leading libraries of Uzbekistan. The results of the reforms on the introduction of information technology in the libraries of the Republic of Uzbekistan are given. An important task is to analyze the main trends and the state of the informatization process in the library-information institutions of the republic and to identify the problems in this area of library activity.

In the commercial and industrial sectors, automatic robotic control mechanisms, which include robots, end effectors, and anchors containing components, are often utilized to enhance service quality. Robotic systems must be installed in manufacturing lines for a variety of industrial purposes, which also increases the risk of a robot, end controller, and/or device malfunction. According to its automated regulation, this may hurt people and other items in the workplace in addition to resulting in a reduction in quality operation. With today's advanced systems and technology, security and stability are crucial. Hence, the system is equipped with fault management abilities for the identification of developing defects and assessment of their influence on the system's activity in the upcoming utilizing fault diagnostic methodologies. To provide adaptive control, fault detection, and state estimation for robotic automated systems intended to function dependably in complicated contexts, efficient techniques are described in this study. This paper proposed a fault detection and state estimation using Accelerated Gradient Descent based support vector machine (AGDSVM) and gaussian filter (GF) in automatic control systems. The Proposed system is called (AGDSVM + GF). The proposed system is evaluated with the following metrics accuracy, fault detection rate, state estimation rate, computation time, error rate, and energy consumption. The result shows that the proposed system is effective in fault detection and state estimation and provides intelligent control automatic control.

The organization of safe and efficient transportation of goods and passengers by air requires the rationalization of the air traffic control system. It is from the operating results of this system that all the qualitative characteristics of the transportation process depend on. At the same time, a special role in this system is given to the control unit inclusive of one or more air traffic control specialists, whose main professional duty is to control air traffic within their area of responsibility based on continuous monitoring of the air situation. As part of this activity, controllers daily make important decisions, the correctness of which directly affects the integrity of aircraft, crews, and passengers. The stated above causes the crucial significance of high-quality training of air traffic control specialists, encompassing the development of skills and abilities, based on specialized training complexes. Therefore, within the framework of this article, an analysis of modern simulators for training controllers was carried out, which made it possible to emphasize their identical structural elements. Additionally, the weaknesses of modern simulator training were identified, associated with the significant labor costs for instructors and the obvious deficiency of reserves for expanding the typical composition of risk events. With reference to the stated above, the key characteristics of an optimally built training complex were worked out, based on the use of modern decision-making support systems in the process of air traffic control specialists training. Adaptation of these models and algorithms will automate the instructor’s position and ensure the dynamism of the system in the field of replenishment of possible air traffic options.

The article discusses the developed automated system for the research of a liquid crystal cell, which consists of hardware and software parts. Unlike previously developed devices for optical measurements of liquid crystal elements, the automated system under consideration provides signal generation accuracy within 0.5% and SFDR noise immunity of at least 80 dB. The hardware part of the system includes the development of a circuit for generating a voltage signal of a certain amplitude and frequency, the formation of signals for controlling the movement of a stepper motor and controlling the intensity of the luminous flux of four laser LEDs, the development and tracing of a printed circuit board. The software part consists in the development of an applied executive algorithm that builds a sinusoidal signal at the output of a digital-to-analog converter of a microcontroller. This example uses the STM32F746IGT6 microcontroller based on the ARM Cortex-M7 core, which has a superscalar architecture with dynamic prediction, a memory protection module, a floating-point computing unit, as well as a direct memory access controller DMA (direct memory access), which is used for accelerated data exchange between memory and peripherals. The DMA is used to quickly control the digital-to-analog converter.

Objective. Currently, access to the information resource of the ATS AS is implemented through the access control subsystem of the information security facility based on the mandatory and discretionary methods of access control developed in the 70s of the last century and requiring improvement. The purpose of the study is to analyze existing methods and, on this basis, select the optimal method for regular users to access information resources of automated systems of internal affairs bodies.Method. System analysis, graph theory method, and verbal (verbal) modeling.Result. A new aspect of the method of access of regular users to information resources of automated ATS systems, based on the use of hierarchical metrics of semantic proximity, is disclosed.Conclusion. The use of a method based on semantic proximity significantly reduces the processing of a large amount of information, respectively, increasing the performance of automated systems.

The article reflects the most important areas of work of scientists and employees of the scientific center “Express” and their contribution to the formation and development of information technology since the founding in 1959 of the Department of computer science of the All-Union Scientific Research Institute of Railway Transport and up to the present.Theoretical foundations of the application of transport cybernetics in the national economy of the country were created by Corresponding Member of the Academy of Sciences of the USSR A. P. Petrov, who was one of the first to use mathematical methods and computing technology in solving transport problems and headed the development in this direction at the institute. The practical work on the creation of the first domestic automated system for selling tickets for trains, called “Express”, was headed by B. E. Marchuk.Since then, the “Express” system has transformed from a local ticketing system at the Kievsky railway terminal in Moscow into a powerful multifunctional international passenger traffic management system that interacts with the ticket reservation systems of European countries.Theoretical and practical developments carried out by the scientific center have resulted in the introduction of new information technologies in the Russian Railways holding and in the railway administrations of the member states of the Commonwealth.At present, the main activities of the staff of the scientific center are the creation of automated control system “Express” of a new generation (ACS “Express” NP) and the system of international integration of passenger transportation Express International.

The sensitivity, specificity and reproducibility of molecular genetic methods of analysis largely depend on the quality of the preliminary preparation of the analyzed samples. During the sample preparation, the tasks of disinfecting pathogenic material, lysing cell membranes, removing compounds and impurities that inhibit the polymerase chain reaction (PCR), as well as concentrating nucleic acids are solved. The purpose of this work is to select modern approaches to sample preparation for the PCR. Among the variety of different methods of sample preparation, the most widespread are the methods based on chemical lysis of cell membranes using chaotropic compounds, followed by purification of nucleic acids by solid-phase extraction using magnetic particles. This approach is implemented both in commercial kits for manual sample preparation and in various automated systems for the isolation of nucleic acids. The analysis of commercially available stations for the isolation of nucleic acids shows that their technical characteristics are similar: the duration of one isolation cycle is 40–90 minutes; the volume of the analyzed samples is from 0.1 to 2.0 ml; the number of simultaneously processed samples max – 96, min – 8. The method of the nucleic acid isolation is the magnetic particles. The main differences are in the type of analyzed samples, and technologies for lysis of the test material and DNA extraction. Our experience in the use of magnetic particle kits for the isolation of nucleic acids, both in stationary and in field laboratories confirms the effectiveness and reliability of this technology. Further development and improvement of the hardware for such work will, obviously, be aimed at miniaturizing the equipment, developing field portable automatic nucleic acid extraction stations, as well as integrating the process of sample preparation and analysis by PCR in one device.

The article considers innovative methods of conducting business activities of an enterprise based on the use of modern information systems, Web technologies, artificial intelligence technologies for creating digital counterparts of an enterprise, managing business processes and managing technical parameters of production. The introduction of innovations at the enterprises of the agro-industrial complex is due to the established stable system of distribution of new technologies based on modern scientific base, programs to support small-scale enterprises and their positioning in the market, for the purpose of developing regional structures, creation of specialized subcomplexes in the structure of processing enterprises, for example, in the food industry enterprises, where the introduction of innovations is associated with lower financial costsThe author gives the introduction of innovations in the implementation of digitalization measures at low-power enterprises on the basis of the development of measurement and computing complexes containing unified automation tools with a wide range of applications, modern software products for collecting and processing data on the progress of the technological process and generatingalarms, as well as diagnostic systems and instructions for the installation of equipment, operating both independently and managed through cloud servers.The paper proposes the measuring and computing complex for monitoring and regulating the parameters of complex processes for monitoring and regulating the parameters of small-scale food production enterprises, shows methods for predicting the properties of products with specified characteristics.The study determines the positive directions of digitalization that ensure the competitiveness and economic development of the enterprises of the agro-industrial complex.

This paper explores whether generalised anxiety disorder (GAD) and depression have any effect on an individual’s explicit general propensity to trust automated systems (trust that is unspecific to any one automated system) and whether those that do have these disorders have an implicit bias towards automated systems over other humans. The human-automated system literature to date has discovered that individual differences in humans, such as self-confidence, mood, and personality types, can influence the human-automated system relationship through human trust and reliance attitudes and behaviour. However, whether suffering from a mental disorder influences an individual’s attitudes towards automated systems generally is yet to be explored. In this study, 184 UK university students responded to online experiments between December 2019 – January 2020 and were subjected to the cultural trust instrument survey and the implicit association test in a between-subjects design to measure their general propensity to trust and implicit association towards automated systems respectively. A two-way ANOVA was performed to evaluate GAD $\times $ depression interaction effects on the dependent variables. Results suggest there was a significant interaction between GAD and depression regarding propensity to trust automated systems but they have little to no influential effect on mean implicit association test scores. Furthermore, those without depression showed a significantly higher trust score when they also had GAD. It can be concluded that GAD and depression have potential critical influence over human-automated system trust, thus creating potential issues with misuse and disuse and must be accounted for in automated system design.

The article is devoted to the assessment of the interaction and communication system for extinguishing large fires in order to create a more effective system for managing the forces and means of extinguishing and ensuring a reliable quality control system for decisions and work performed. Research on the state of the issue described in the article is planned to be used to prepare methods for managing forces and strategy in large fires, this technique can be adopted normative legal acts of the corresponding Federal state Executive bodies. Most of the Russian Federation’s forest resources are located in remote and inaccessible areas. This leads to the fact that some forest fires turns into large ones. Despite the fact that large forest fires in the Russian Federation account for only about 8–18 % in number, the total area covered by fire is about 90 %. Improving the effectiveness of fighting large forest fires is of primary importance and the amount of annual damage to the budget of our country will depend on the correct organization of this work. To date, timely and reliable formation of scientific and analytical information for making operational management decisions in the organization of extinguishing large forest fires is extremely important. The article is based on the results of evaluating information support for extinguishing large forest fires based on the analysis of the use of the most effective technological solutions in the field of managing the forces and means of extinguishing that are used in the elimination of large forest fires. This made it possible to make sure that modern effective models of decision support systems (both in the military and civil sectors) are available in Russia and they can be successfully adapted to the tasks of fighting large forest fires. Modern capabilities of Rosleskhoz should be actively used in the Russian decision-making system for predictive modeling of the spread of a large fire and the presentation of other actual and calculated parameters.

The article defines large territorially distributed automated systems, which include systems that collect and process information from spatially spaced sensors on objects. Examples of such automated systems are military systems, such as a missile attack warning system, a space control system, strategic and non-strategic missile defense systems, and civil systems, such as the state automated Control system, the air traffic control system and other systems. The purpose of these systems is the continuous monitoring of the state of a set of certain objects, the environment of their functioning, the constant assessment of the parameters of objects, the identification of dangerous situations in the behavior of objects and the environment, as well as the development of measures to reduce the level of possible security threats and eliminate dangerous situations.The typical structure of large territorially distributed automated systems includes sources and consumers of information, telecommunication facilities, as well as a center for processing input data and preparing information for consumers. The sources of information are operators, technical means of observation and specialized measuring instruments. Telecommunication means of big territorially distributed automated systems are formed in two ways. The first option uses existing global data net-works. In the second variant, self-made data transmission networks are formed on the basis of specially created means of data transmission and the use of dedicated data channels. The center of input data processing and information preparation contains a complex of automation tools and personnel providing maintenance, repair and operation.The functions and the most significant hardware and software components of large territorially distributed automated systems are presented. The main indicators of quality of their functioning and stages of life cycle are characterized: development of requirements, creation of a prototype, certification, mass production, operation, modernization, the end of operation and utilization.

Conventional models in the intelligent transportation system (ITS) are confronted by large computational overheads and how they react during real-time scenarios. To appropriately manage the communication process in real-time, a trust-based mechanism can provide an efficient approach to acclimatize its deeds based on indecision sensory information. However, the computational models are not fully demoralized by the businesses owing to the lack of automated integration. In this study, we perform agent-based modeling (ABM) and population-based modeling (PBM) in the ITS mechanism during data transmission and record exchange for real-time communication. In addition, a trust evaluation process is performed to legitimize each device with the integration of ABM and PBM models. The simulation results show that the proposed mechanism is 89% more efficient than baseline methods in various networking scenarios, such as message alteration, distributed denial of service attacks, and information falsification threats.

Experiences with technology often are described as exciting and outstanding, for instance, in relation to novel technologies at home or at work. In this article, we aim to complement this perspective by emphasizing people’s mundane and ordinary experiences with technology, that is, unremarkable experiences happening in the background of people’s attention. Based on our investigations of user experience in a semiconductor factory, we show how such ordinary experiences are substantial in workers’ everyday interactions with technology, which are mainly shaped by repetitive activities and routines. However, current conceptions of user experience seem to overlook those mundane experiences and how they can contribute to positive experiences with technology, as well as work engagement in the factory. In this article, we describe how ordinary experiences can be understood and described to amend current user experience conceptions by discussing theoretical, methodological, and design consequences.

Оскільки інтенсивний комерційний розвиток аеропортів робить їх основними генераторами зростання міст, то вони стають одними з головних сфер зайнятості, торгівлі та бізнесу. Актуальність досліджуваної теми зумовлена нагальною необхідністю виробничих змін Запорізького аеропорту з огляду на провідну роль міжнародних аеропортів в розвитку світової економіки. Предметом дослідження є сучасний стан розвитку Запорізького аеропорту. Метою статті є дослідження питань розвитку ефективної транспортно-повітряної інфраструктури Запорізького регіону. Базовими принципами дослідження виступають системний та порівняльний методи, використані аналітичний, структурний та функціональний підходи. Наукова значущість полягає в дослідженні можливих шляхів вдосконалення діяльності досліджуваного підприємства в сучасних умовах. Як висновок наводиться необхідність активізації процесів інноваційної діяльності Запорізького аеропорту, а також запропоновано комплексний поетапний розвиток даного підприємства. На практиці це сприятиме створенню сприятливого інвестиційного клімату, залученню інвестицій та створенню великого центру бізнес активності у Запорізькому регіоні Purpose. The purpose of the article is to study the development of efficient transport and air infrastructure in the Zaporozhye region. Design / methodology / approach. The basic principles of research are system and comparative methods, analytical, structural and functional approaches are used. Findings. As a conclusion, it is necessary to activate the processes of innovation activity of Zaporozhye airport, as well as the complex phased development of this enterprise. Research limitations / implications. The scientific significance lies in the study of possible ways of improving the activity of the enterprise under investigation in modern conditions. Originality/value. In practice, this will help create a favorable investment climate, attract investment and create a major business activity center in the Zaporozhye region

The spread of automated vehicles (AVs) is expected to disrupt our mobility behavior. Currently, a male bias is prevalent in the technology industry in general, and in the automotive industry in particular, mainly focusing on white men. This leads to an under-representation of groups of people with other social, physiological, and psychological characteristics. The advent of automated driving (AD) should be taken as an opportunity to mitigate this bias and consider a diverse variety of people within the development process. We conducted a qualitative, exploratory study to investigate how shared automated vehicles (SAVs) should be designed from a pluralistic perspective considering a holistic viewpoint on the whole passenger journey by including booking, pick-up, and drop-off points. Both, men and women, emphasized the importance of SAVs being flexible and clean, whereas security issues were mentioned exclusively by our female participants. While proposing different potential solutions to mitigate security matters, we discuss them through the lens of the feminist HCI framework.

Purpose. The paper is aimed to analyze the functioning of the existing railway informational system, as the data storage, consideration of the ways to changeover to intelligent management system, including the application of semantic approach. It is necessary to change the paradigm of automated traffic management; this determines changing the paradigm in railway operation management. The development and introduction of new Business-Intelligence-type system requires the formalized knowledge on railway transportation process to be implemented, including in the form of ontology as the model and means to formalize the knowledge. New knowledge requires using the terms and concepts to describe the new processes and management objects in railway operations. Methodology. Formalizing the knowledge one should abstract away from classical definitions such as marshaling or freight station, train station, division station, dead-end station, railway junction, railway hub etc. Unified Modeling Languages for engineering the automated systems use the definitions: the objects’ categories, the class diagrams, statechart diagrams, sequence diagrams, activity diagrams, component diagrams, link diagrams in properties etc. These concepts enable formalizing the knowledge, bringing to homogeneous representing and using them for modeling the management processes of goods delivery. Findings. The data on timing the events of goods delivery process, breakings of schedule are taken into account in set-theoretical model on scripting scenarios for goods delivery process. One of the concepts in the model on breaking of schedule (from the knowledge base of the system ASK VPUZ-E enables to take into account the influence of possible factors and the real railway operations conditions. Originality. The ways to formalize knowledge on railway transportation process as the major premise to form intelligent informational software for management system were analyzed. The set-theoretical models on goods delivery management for scripting goods delivery process’ scenarios have been developed in the paper, the examples of using the means of object-oriented modeling to construct algorithm for technological processes have been given as well. Practical value. The author suggests new terms, definitions and concepts describing the logistic business processes and enabling to changeover to formalizing the knowledge and to forming the conditions of intelligent management system of goods delivery on railways.

Power companies usually answer the increase in power demand by building new generation facilities. Nevertheless, an efficient use of energy could reduce and delay the costs of investment in new power plants. This paper shows a software system to manage transformers and evaluate losses when they work with zero loads. This system contributes to reduce the waste of energy with some simple actions such as shutting off an unused transformer or reconnecting disabled equipment based on the customer’s demand. It uses real time measurements collected from Intelligent Electronic Devices as a base for software decisions. It also measures and reports the total power saving.

A model predictive control (MPC) scheme for a Schunk PowerCube robot is derived in a structured step-by-step procedure. Neweul-M2 provides the necessary nonlinear model in symbolical and numerical form. To handle the heavy online computational burden concerning the derived nonlinear model, a linear time-varying MPC scheme is developed based on linearizing the nonlinear system concerning the desired trajectory and the a priori known corresponding feed-forward controller. Camera-based systems allow sensing of the robot on the one hand and monitoring the environments on the other hand. Therefore, a vision-based MPC is realized to show the effects of vision-based control feedback on control performance. A semi-automatic trajectory planning is used to perform two meaningful experimental studies in which the advantages and restrictions of the proposed (vision-based) linear time-varying MPC scheme are pointed out. Everything is implemented on a slim, low-cost control system with a standard laptop PC.

As the reliance upon automated systems in the livestock industry increases, technologies need to be developed which can be incorporated into these systems to monitor animal health and welfare. Infrared thermography (IRT) is one such technology that has been used for monitoring animal health and welfare and, through automation, has the potential to be integrated into automated systems on-farm. This study reports on an automated system for collecting thermal infrared images of calves and on the development and validation of an algorithm capable of automatically detecting and analysing the eye and cheek regions from those images. Thermal infrared images were collected using an infrared camera integrated into an automated calf feeder. Images were analysed automatically using an algorithm developed to determine the maximum eye and cheek (3 × 3-pixel and 9 × 9-pixel areas) temperatures in a given image. Additionally, the algorithm determined the maximum temperature of the entire image (image maximum temperature). In order to validate the algorithm, a subset of 350 images analysed using the algorithm were also analysed manually. Images analysed using the algorithm were highly correlated with manually analysed images for maximum image (R2 = 1.00), eye (R2 = 0.99), cheek 3 × 3-pixel (R2 = 0.85) and cheek 9 × 9-pixel (R2 = 0.90) temperatures. These findings demonstrate the algorithm to be a suitable method of analysing the eye and cheek regions from thermal infrared images. Validated as a suitable method for automatically detecting and analysing the eye and cheek regions from thermal infrared images, the integration of IRT into automated on-farm systems has the potential to be implemented as an automated method of monitoring calf health and welfare.

Problem-orientated to the innovative activity, computer-aided systems of production engineering (CASPE) integrates design, manufacture, and organization activities using the interrelated innovation principles thus leaning the innovative activity towards the creation of innovative products and technological innovations of high science and technology level and efficiency. In this situation the innovative activity uses in practice not only the newest experience, but also the science laws and consequences, that is, in particular, “Science of Innovations”. The mentioned science laws explain wave dynamics of technical (technological) systems development. In the course of innovation activities and/or innovation designing a modification of continuously acting technological system, usually, causes its developing and growing upwards by Sshaped curve. Changing a principle of action changes S-shaped curve development (Fig. 1). If such changes are within the certain “trace tube” we are entitled to state the steady system development.Analysis of changing target function of technological system within the “trace tube” of its steady development characterizes its growing wave dynamics (Fig. 1) using the S-shaped curves (sigmoid type relations). S-shaped innovative development relations of technological systems are, usually, explained by different mathematical models, each being in compliance with the certain process of science and technology. Singular innovative project management using the S-shaped curves can be explained by the following example (Fig.2).To use such management technique it is very important to know the mathematical models of S-curves for different types of innovation projects. That is why we consider given S-shaped relations in-detail for:- developing the high and critical technologies during R&D implementation using the cutting-edge CASSR (computer-aided systems of scientific research) of high and critical technologies in innovation designing;- implementing the high and critical technologies when developing the innovation projects for renewal of manufacturing process or equipment to produce innovative products in computeraided systems of production engineering (CASPE).

In Earth Science, image cross-correlation (ICC) can be used to identify the evolution of active processes. However, this technology can be ineffective, because it is sometimes difficult to visualize certain phenomena, and surface roughness can cause shadows. In such instances, manual image selection is required to select images that are suitably illuminated, and in which visibility is adequate. This impedes the development of an autonomous system applied to ICC in monitoring applications. In this paper, the uncertainty introduced by the presence of shadows is quantitatively analysed, and a method suitable for ICC applications is proposed: The method automatically selects images, and is based on a supervised classification of images using the support vector machine. According to visual and illumination conditions, the images are divided into three classes: (i) No visibility, (ii) direct illumination and (iii) diffuse illumination. Images belonging to the diffuse illumination class are used in cross-correlation processing. Finally, an operative procedure is presented for applying the automated ICC processing chain in geoscience monitoring applications.

Coagulase-negative staphylococci (CoNS) are an important cause of nosocomial bacteremia, specially in patients with indwelling devices or those submitted to invasive medical procedures. The identification of species and the accurate and rapid detection of methicillin resistance are directly dependent on the quality of the identification and susceptibility tests used, either manual or automated. The objective of this study was to evaluate the accuracy of two automated systems MicroScan and Vitek - in the identification of CoNS species and determination of susceptibility to methicillin, considering as gold standard the biochemical tests and the characterization of the mecA gene by polymerase chain reaction, respectively. MicroScan presented better results in the identification of CoNS species (accuracy of 96.8 vs 78.8%, respectively); isolates from the following species had no precise identification: Staphylococcus haemolyticus, S. simulans, and S. capitis. Both systems were similar in the characterization of methicillin resistance. The higher discrepancies for gene mec detection were observed among species other than S. epidermidis (S. hominis, S. saprophyticus, S. sciuri, S. haemolyticus, S. warneri, S. cohnii), and those with borderline MICs.

INTRODUÇÃO: A tuberculose permanece um problema de saúde pública mundial. OBJETIVO: Avaliar um sistema de diagnóstico automatizado de tuberculose, comparando-o com baciloscopia e cultura em meio de Lowenstein-Jensen. MÉTODO: Estudo comparativo entre os resultados obtidos no sistema automatizado, baciloscopia do escarro e em meio de Lowenstein-Jensen, em 844 amostras de escarro de setembro a dezembro de 1999, em centro de referência para tuberculose em São Paulo (SP). RESULTADOS: Das 844 amostras, 27,1% mostraram-se positivas para bacilo álcool-acidorresistente e 72,9% negativas. Nos cultivos em Lowenstein-Jensen, 34,7% foram positivas e 63% negativas; no sistema automatizado, 37,1% foram positivas e 56,9% negativas. Observou-se sensibilidade de 98,1% e 91.9% no sistema automatizado e no Lowenstein-Jensen, respectivamente. A especificidade e o valor preditivo positivo foram de 100% nos dois métodos. O valor preditivo negativo foi de 98,9% no sistema automatizado e de 95,5% no Lowenstein-Jensen. A acurácia foi de 99,3% no sistema automatizado e 97% no Lowenstein-Jensen e o Kappa de 0,99 no sistema automatizado e 0,94 no Lowenstein-Jensen. O tempo médio de detecção das micobactérias no sistema automatizado (10,5 dias) apresentou diferença estatística significativa quando comparado com o método de Lowenstein-Jensen (34,7 dias). CONCLUSÃO: O rendimento da cultura com o sistema automatizado apresentou diferença estatística significativa quando comparado com o meio de Lowenstein-Jensen. O tempo médio de detecção das micobactérias foi significativamente reduzido no sistema automatizado. O rendimento do sistema automatizado justifica sua utilização em unidade de referência ambulatorial para a tuberculose em São Paulo.BACKGROUND: Tuberculosis continues to be a global health problem. OBJECTIVE: To evaluate an automated system designed to diagnose tuberculosis, comparing it to sputum microscopy and culture in Löwenstein-Jensen medium. METHOD: A comparative study using 844 sputum samples, collected between September and December of 1999 at a reference center for tuberculosis in São Paulo, Brazil, to draw distinctions between the results obtained through the use of the automated system and those obtained through sputum microscopy and culture in Löwenstein-Jensen medium. RESULTS: Of the 844 samples evaluated, 27.1% tested positive for acid-fast bacilli, and 72.9% tested negative. In Löwenstein-Jensen culture, 34.7% were positive and 63% were negative, compared with 37.1% positivity and 56.9% negativity using the automated system. Sensitivity was 98.1% for the automated system and 91.9% for Löwenstein-Jensen culture. Specificity and positive predictive value were 100% for both methods. Negative predictive value was 98.9% for the automated system and 95.5% for Löwenstein-Jensen culture. The degree of accuracy was 99.3% for the automated system and 97% for Löwenstein-Jensen culture, and the Kappa was 0.99 for the automated system and 0.94 for Löwenstein-Jensen culture. The difference between the mean time to detection of mycobacteria using the automated system (10.5 days) and that found using Löwenstein-Jensen culture (34.7 days) was statistically significant. CONCLUSION: The difference between the culture yield obtained using the automated system and that achieved with Löwenstein-Jensen culture was statistically significant. Mean time to detection of mycobacteria was significantly shorter with the automated system. The higher yield provided by this new system justifies its use in a reference center for tuberculosis in São Paulo

The article describes the technology, applicable in automated library systems and based on collaborative filtration, for forming recommendation lists.

Motivados por la necesidad de exponer nuevas experiencias en el trabajo con las autopsias, luego de escribir el libro "La autopsia. Garantía de calidad en la Medicina" y concluir la investigación "Evaluación de la calidad de los diagnósticos premortem en autopsias realizadas en Cuba entre 1994 y 2003", se presenta este trabajo con el propósito de que pueda ser útil a los interesados en el tema y acercarse al objetivo final: lograr el máximo aprovechamiento de la autopsia. Se expone la situación de la autopsia en el mundo y en Cuba. Se enfatiza en los logros alcanzados en el país, donde se incluyen los hospitales militares, las dificultades atravesadas y se señala el camino a seguir para disminuir la morbilidad y mortalidad, y lograr el objetivo mayor: aumentar en cantidad y calidad la vida de la población.