Automatic System Research Articles

Algorithm for Precise Payload Drop From FPV Drone with Account of Wind Strength and Automatic Position Correction

The work is devoted to the development of an automatic system for dropping cargo from an first-person view drone. An analysis of approaches to the construction of this type of system was performed. It is proven that this problem has not been fully solved, which requires the development of new approaches. In order to increase accuracy, it is proposed to use mathematical models that describe the process of cargo unloading. Mathematical models are given that connect such variables as Height, wind speed, drone speed, cargo weight, cargo surface area, wind direction angle relative to the drone, air density. The use of the obtained mathematical models allows you to calculate the coordinates of the reset point. The developed approach was tested in real conditions. The obtained results showed a significant improvement in the accuracy of dropping the load in the presence of a constantly acting wind.

Escherichia coli, an important Uropathogen: Characteristics and antimicrobial susceptibility pattern at Prof. Dr. I.G.N.G. Ngoerah General Hospital, period January 2020 – December, 2021

Background: Urinary tract infections (UTIs) are among the most common infections globally, often treated empirically with broad-spectrum antibiotics without prior culture and sensitivity testing. This practice has contributed to the rise in antibiotic resistance. Escherichia coli (E. coli) is the primary pathogen in uncomplicated UTIs, accounting for 70–90% of cases. However, other bacteria such as Klebsiella pneumoniae, Proteus mirabilis, and Enterococcus faecalis are also significant, especially in complicated or healthcare-associated UTIs. This study examines the resistance patterns of E. coli in UTI cases. Method: A descriptive cross-sectional study was conducted using secondary data from medical records of UTI patients treated at Prof. Dr. I.G.N.G. Ngoerah General Hospital from January 2020 to December 2021. E. coli isolates were identified, and antibiotic sensitivity tests were performed using the VITEK® 2 compact automatic system, with antimicrobial sensitivity and resistance determined according to Clinical and Laboratory Standards Institute (CLSI) guidelines. Result: Analysis of 639 UTI patients revealed that E. coli exhibited high resistance to cefixime (13.3%), ciprofloxacin (23.8%), and trimethoprim-sulfamethoxazole (35.2%). The highest levels of susceptibility were observed with Tigecycline, Meropenem, and Ertapenem, with rates ranging from 99.2% to 99.8%. The demographic data showed a higher incidence of UTIs in female patients (70.9%) compared to males (29.1%), with the majority of cases occurring in adults (94.52%). Additionally, 52.26% of the E. coli isolates were ESBL-producing strains, complicating treatment options. Conclusion: The study underscores the urgent need for judicious antibiotic use, guided by culture and sensitivity testing, to combat the rising threat of antibiotic-resistant UTIs. Tigecycline, Meropenem, and Ertapenem should be prioritized in treatment protocols for multidrug-resistant cases. Continuous surveillance and the development of new antimicrobial agents are essential to address this escalating public health challenge

СИСТЕМА АВТОМАТИЧЕСКОГО ПОСТРОЕНИЯ РЕГУЛИРОВОЧНЫХ ХАРАКТЕРИСТИК ПЕРЕГОНОВ ДЛЯ ЦЕНТРАЛИЗОВАННЫХ ИНТЕЛЛЕКТУАЛЬНЫХ СИСТЕМ УПРАВЛЕНИЯ ДВИЖЕНИЕМ ПОЕЗДОВ

the relevance of developing a system for automatic construction of regulating characteristics of railway sections for centralized train traffic control is discussed. Regulating characteristics allow determining the minimum permissible interval for train departure from the station, considering the given travel time of two consecutively moving trains and the specified dwell time of the leading train. The principles of constructing an automatic system for generating these characteristics are presented. Examples of the results of constructing adjustment characteristics for metro lines are provided.

Reducing life cycle environmental impacts of milk production through precision livestock farming

In recent decades, the livestock sector has significantly improved its efficiency, productivity, and environmental sustainability. Precision Livestock Farming (PLF) represents a driver in this direction, since it enables to monitor individual animals and herds, and supports the farmer in making better decisions. Although the benefits are clear on a livestock perspective, it is difficult to quantify the environmental benefit of having technology on farm, mostly due to the complexity of collecting data on the same farm before and after a certain solution.In this context, this paper focuses on the assessment of the environmental sustainability of a case-study Italian dairy cattle farm where different technologies were installed one by one: first a mechanical ventilation system (MV) and second an automatic milking system (AMS), without introducing other significant changes to the farm management and practices in the meantime. The environmental impact of milk production on the farm was quantified through the Life Cycle Assessment (LCA) method, and the initial farm configuration was compared with the two scenarios in which each technology was incorporated. Fat and protein corrected milk (FPCM) was used as Functional Unit, and a cradle to farm gate system boundary and biophysical allocation method were selected. This enabled to provide valuable insights for stakeholders about the effect on the environmental sustainability of the use of the two technologies. The results show that for all the evaluated impact categories there is an environmental benefit of the improved scenarios. The biggest benefit can be observed with the installation of mechanical ventilation, to which correspond benefits in terms of animal health, welfare and productivity. Then, also AMS entails sustainability improvements, mainly linked with increased efficiency and productivity. In conclusion, the use of technology on dairy farms improves not only the farm efficiency and the animal management, but also the environmental sustainability. Furthermore, the rapid technological advancements may further enhance this positive trend in reducing the contribution of livestock farming to the environmental impacts provided that farmers adopt them.

Ventilator-associated pneumonia caused by a new-found opportunistic fungal pathogen—Myceliophthora heterothallica: a case report

BackgroundMyceliophthora heterothallica belonging to Myceliophthora is considered as an environmental fungus and has not been reported to be pathogenic or colonizing in recent literature. The present case firstly reports a ventilation-associated pneumonia caused by Myceliophthora heterothallica among the aged adult.Case presentationA 67-years-old Asian female patient suffering from a sudden disturbance of consciousness for 3 h was admitted to our hospital. Cardiac arrest occurred during emergency transport, and sinus rhythm was restored after cardiopulmonary resuscitation. Invasive mechanical ventilation was given to this patient for respiratory failure. After mechanical ventilation, the lung CT images showed multiple cuneiform nodules arranging subpleural accompanying with ground-glass opacity. On the 5th day of mechanical ventilation, Myceliophthora heterothallica was cultured from endotracheal aspirates. Two methods, namely automatic microbial identification system and internal transcribed spacer sequencing were employed to identify this fungus. The present case firstly uncovered the colonization ability and pathogenicity of Myceliophthora heterothallica in the respiratory tract. After 28d of treatment with piperacillin-tazobactam, this patient weaned from the ventilator and recovered from consciousness with lung infection disappearance.ConclusionsThis is the first case report of ventilation-associated pneumonia in the aged patient caused by Myceliophthora heterothallica. This current case is worth for the clinical diagnosis and treatment of Myceliophthora heterothallica infection, and also enriches new pathogenic species found of thermothelomyces species.

Prospects of autonomous railway transport development

The implementation of unmanned train control systems offers a number of advantages, such as increasing the capacity of railway lines and traffi c volumes, reducing the ‘human factor’, as well as reducing operating costs. The paper considers the challenges arising from the use of automatic train control systems, and presents the prospects for the implementation of automatic technologies in railway transport for various railway systems. The social and economic aspects of changing professional activities in railway transport are described. Grades of automation applicable to surface urban railwaytransport are presented. The issues of proving the functional safety of machine vision systems as part of the train traffic control system and determining their level of safety completeness are discussed. Examples of railway transport automation in Russia and other countries are given. Basic scenarios of automatic control system operation describing normal and abnormal situations are formulated. In conclusion, the levels of technological readiness of the reviewed solutions in the fi eld of train traffic automation are defi ned. The tasks faced by railway companies in implementing these technologies are outlined, and possible ways of overcoming obstacles to the introduction of automatic systems are proposed, taking into account the current political situation.

Development of an Automatic Liquid Dosing System in Microliter Scale

The goal of this study is to design a novel automatic liquid dosing system for liquid sampling at the microliter level. For this purpose, a mechatronics system is designed to position a syringe at the desired position in the workspace and then drive its piston to inject the liquid to be sampled. Then, an application-specific algorithm is developed to be able to prepare samples in 3x3, 4x4, and 5x5 sample container arrays with a desired volume. The performance tests are conducted for preparing samples with up to three different liquids. The repetitive experiments are performed for 50 and 100 µL sampling volumes. The results indicated that it is possible to dose a single liquid with the highest average deviation of 3.9%. Moreover, it is found that it is possible to prepare a sample with a mixture of three liquids by the highest average deviation from the reference value of around 3.4% when the targeting sampling volume is 250 µL for each liquid.

STRUCTURE OF THE AUTOMATED CONTROL SYSTEM OF TECHNOLOGICAL PARAMETERS OF TREATMENT FACILITIES OF THE CITY SEMEY

Increasing the efficiency of control of treatment facilities can be achieved by automation of control at the stages of observation, collection, processing and analysis of information by means of mathematical data analysis packages, implementation of automated control systems of technological processes.This article is devoted to the issues of technical modernization of automatic control system of water disposal in Semey city. The need to modernize the concept of building the ACS has arisen in connection with the technical re-equipment of production and introduction of new energy-saving technologies in it.The hypothesis of the research suggests the possibility of improving the efficiency of wastewater treatment facilities of Semey city through the use of modern methods of collection and transmission of technological parameters to the control panel of the dispatcher in order to make operational decisions on the management of technological and technological process of wastewater treatment based on monitoring of equipment operation. Due to the complexity of the whole complex of treatment facilities, the main sewage pumping station (GKNS-2) and air blower pumping station (ABPS) were selected as objects for the development of automated control system of technological parameters (ACS TP).The article considers the proposed structural scheme of the automated system of control of technological parameters of treatment facilities of Semey city, gives a description of each level of the system and the principle of their interaction.

Parametric correction in the control system of the electric propulsion of autonomous underwater vehicles affected by random inputs

The paper deals with the problem of controlling a DC propulsion motor of an autonomous underwater vehicle using a bidirectional non-isolated DC-DC converter. An automatic speed control system with a parametric controller was developed in the Matlab / Simulink package. To reduce energy conversion stages, dc-dc converters are often used to control dc motors AUV. The result of the work is an adaptive control system for the speed of the AUV propeller, which would provide high accuracy for a wide range of speeds and at the same time limit the maximum current and voltage at the armature. The indicators of the quality of performance in various modes of operation were determined, maps of the controller settings were compiled, and parametric correction was introduced. The operation of the system is analyzed and drawbacks are eliminated, such as voltage surges when switching from one speed to another, a decrease in overshoot and settling time. The performance of the system is analyzed under the conditions of random inputs from the propeller. The description of the laboratory stand for the study of the control system is given. A description of the laboratory study of the operation of the "DC converter—engine" system under conditions of random fluctuations in the moments on the motor shaft is given. It is shown that the proposed system has shown itself well under laboratory conditions and the experimental results are consistent with modeling in Matlab / Simulink.

High-uniformity liquid-cooling network designing approach for energy storage systems by graph-coupled genetic algorithm

Electrochemical battery energy storage stations have been widely used in power grid systems and other fields. Controlling the temperature of numerous batteries in the energy storage station to be uniform and appropriate is crucial for their safe and efficient operation. Thus, effective thermal management is required. In this work, an approach for rapid and efficient design of the liquid cooling system for the stations was proposed. A hydraulic solution model for the liquid-cooling network was established based on graph theory principles, and the genetic algorithm was employed for automatic system optimization to achieve high cost-effectiveness and ideal temperature distribution. Experiments were conducted to validate the accuracy of the hydraulic model and evaluate the efficacy of the optimization strategy. The flow rate calculated from the hydraulic model agreed well with the experiments, with a discrepancy smaller than 3.5 %, and the uniformity of flow rates was improved to as high as 70 % after the optimization. Furthermore, the applicability of this approach was also confirmed across various sizes of energy storage systems.

Model-agnostic confidence measurement for aggregating multimodal ensemble models in automatic diagnostic systems

Automatic diagnostic systems (ADSs) have been garnering increased attention because they can alleviate the workload of clinicians by assisting in diagnosis and offering low-cost access to healthcare for people in medically underserved areas. ADS can suggest potential diseases by analyzing a patient's self-report. Previous research on ADS has leveraged diagnostic case data from various patients and medical knowledge to diagnose diseases, with multimodal ensemble methods proving particularly effective. However, the existing multimodal ensemble method combines the probabilities of different models in the aggregating process, which can not properly combine the probabilities that are produced by different criteria. To address these issues, we propose an effective aggregation framework for multimodal ensembles that can properly aggregate model-agnostic confidence scores and predictions from each model. Our framework transforms probability scores from different criteria into unified aggregation rule-based scores and reflects the gap between the probabilities that may be blurred in the aggregation process through the confidence score. In particular, The proposed confidence measurement method employs a post-analysis approach with the developed model or algorithm, making it adaptable in a model-agnostic manner and suitable for multimodal ensemble learning that utilizes heterogeneous prediction results. Our experimental results demonstrate that our framework outperforms existing approaches by more effectively leveraging the strengths of each ensemble member.

Comparing the Performance of Automatic Milking Systems through Dynamic Testing Also Helps to Identify Potential Risk Factors for Mastitis.

Automatic milking systems (AMSs) are revolutionizing the dairy industry by boosting herd efficiency, primarily through an increased milk yield per cow and reduced labor costs. The performance of milking machines, whether traditional or automated, can be evaluated using advanced vacuum meters through dynamic testing. This process involves scrutinizing the system and milking routine to identify critical points, utilizing the VaDia™ logger (BioControl AS, Rakkestad, Norway). Vacuum recordings were downloaded and analyzed using the VaDia Suite™ software under the guidance of a milking specialist. Access to data from AMSs across various manufacturers and herds facilitated a retrospective study aimed at describing and comparing key milk emission parameters for different AMS brands while identifying potential mastitis risk factors. Using the proper statistical procedures of SPSS 29.1 (IBM Corp., Armonk, NY, USA), researchers analyzed data from 4878 individual quarter milkings from cows in 48 dairy herds. Results indicated a significant variability in milking parameters associated with quarter milk yield and AMS brand. Notably, despite AMSs standardizing teat preparation and stimulation, this study revealed a surprisingly high frequency of two major mastitis risk factors-bimodality and irregular vacuum fluctuations-occurring more frequently than in conventional milking systems. This study, one of the few comparing different AMS brands and their performance, highlights the crucial role of dynamic testing in evaluating AMS performance under real-world conditions.

Mechatronic technological system based on CNC and intelligent mechatronic mechanism

A mechatronic technological system (MTS) has been developed. It consisting of a CNC metal-cutting machine tool and a mechatronic spindle, made on the basis of an intelligent mechatronic mechanism (IMM). The main elements of the technological system – the CNC and IMM devices – are parts of a single hierarchical, two-level control system, representing, respectively, the upper and lower control levels in this system. The upper control level – the CNC device – ensures stabilization of the kinematic parameters of machining (displacement, speed, acceleration) and their software change in accordance with the CNC control program. The lower control level – the IMM device – ensures stabilization of the power parameters of mechanical machining (cutting axial force and torque) and their software change in accordance with the technological requirements for the surface quality and the physical-and-mechanical state of the surface layer of the machined parts. At both control levels (the upper and lower ones), closed automatic control systems “by deviation” of the adjustable kinematic (upper control level) and power (lower control level) parameters of mechanical machining are functioning. Moreover, the automatic control system of the lower control level of the hierarchy in relation to a similar automatic control system of the upper control level, implements the method of automatic control “by disturbance”. This, in addition to directly ensuring surface finish and surface integrity, allows improving the quality of stabilization of kinematic cutting parameters at the upper control level. Experimental studies of MTS were carried out when machining parts from various materials (steel, polymer composite materials, superhard crystals and stones, other difficult-to-machine materials).

The role of technology in modern industrial processes: a comparative analysis of automated, automatic and mechanical systems

In the modern technological sphere, systems are categorized into various types based on their level of complexity and functional capabilities. The primary types are mechanical, automatic, and automated systems. Each of these types has its unique characteristics and areas of application. Mechanical systems are the simplest of all. They consist primarily of physical components such as gears, levers, and springs, which interact to perform specific tasks. These systems typically lack built-in control or regulation mechanisms, and their operation is based on basic mechanical principles. Examples of mechanical systems include simple clock mechanisms or traditional measuring devices. Automatic systems represent an evolutionary step beyond mechanical systems, as they include elements for automatic control. These may be electrical or electronic components that enable the system to perform certain operations without direct human intervention. For example, automatic doors or thermostats that regulate room temperature are examples of such systems. They can respond to changing conditions and perform tasks based on predefined parameters. Automated systems, in turn, are the most complex and integrated. They combine automatic control with software and advanced management systems, allowing them to adapt to changing environmental conditions and make decisions independently. Automated systems may include elements of artificial intelligence and machine learning, enabling them to perform complex tasks such as data processing or optimizing production processes. Examples include industrial robotic lines or management systems in distribution networks. Thus, the main differences between these systems lie in their level of complexity and functional capabilities: mechanical systems are based on simple physical principles, automatic systems contain elements of automatic control, and automated systems provide a high level of integration and autonomy.

Depressurization strategy of China's advanced pressurized water reactor under typical accidents

Advanced pressurized water reactor was simulated using system analysis program. The depressurization strategy for the automatic depressurization system (ADS) under typical ADS-triggering accidents (2-inch/10-inch cold leg break, inadvertent opening of the ADS, DVI pipeline break) was investigated. The results show that after these accidents, ADS can ensure the operation of the three types of safe injection tanks, with high redundancy and inherent safety. The multi-stage design of ADS aids the sparger in maintaining a stable critical jet state. In 10-inch cold leg break accident, the sparger cannot reached the critical jet state under all of pipeline fault conditions. From a system point of view, adjusting the pipeline design of ADS is necessary to avoid long-term condensation oscillation of the sparger in some accidents. From a design perspective of the local equipment, the nozzle structure of the sparger should attenuate the dynamic load caused by the condensation oscillation and back-attack phenomenon.

Analysis of Low-Carbon, Energy-Saving, and Emission Reduction Models Based on Rail Transit

It is difficult to define scientific applicability conditions when dealing with different evaluation objects and scope. This article is based on multi-source big data such as the Automatic Fare Collection System (AFC) of urban rail transit, comprehensively considering the multidimensional impact of urban rail transit on the urban transportation system, and conducting a quantitative analysis of the energy-saving and emission reduction effects of urban rail transit. This study adopts a traffic emission model based on specific driving forces and a traffic demand prediction model, coupling the model and data to establish an urban rail transit energy conservation and emission reduction evaluation model suitable for different urban rail transit setting scenarios. Finally, this study selected six districts in Beijing as model application cases and used a combination of RP (display preference) survey and SP (state preference) survey to complete model parameter calibration for application cases.

Evaluation of Focus Measures for Hyperspectral Imaging Microscopy Using Principal Component Analysis.

An automatic focusing system is a crucial component of automated microscopes, adjusting the lens-to-object distance to find the optimal focus by maximizing the focus measure (FM) value. This study develops reliable autofocus methods for hyperspectral imaging microscope systems, essential for extracting accurate chemical and spatial information from hyperspectral datacubes. Since FMs are domain- and application-specific, commonly, their performance is evaluated using verified focus positions. For example, in optical microscopy, the sharpness/contrast of visual peculiarities of a sample under testing typically guides as an anchor to determine the best focus position, but this approach is challenging in hyperspectral imaging systems (HSISs), where instant two-dimensional hyperspectral images do not always possess human-comprehensible visual information. To address this, a principal component analysis (PCA) was used to define the optimal ("ideal") optical focus position in HSIS, providing a benchmark for assessing 22 FMs commonly used in other imaging fields. Evaluations utilized hyperspectral images from visible (400-1100 nm) and near-infrared (900-1700 nm) bands across four different HSIS setups with varying magnifications. Results indicate that gradient-based FMs are the fastest and most reliable operators in this context.

Developing a Machine-Learning-Based Automatic Incident Detection System for Traffic Safety: Promises and Limitations

Developing a Machine-Learning-Based Automatic Incident Detection System for Traffic Safety: Promises and Limitations

The potential relationship between EasyNAT system Tt values and Cobas z480 Ct values in the detection of SARS-Cov-2

ObjectivesThis study aimed to evaluate the potential relationship between the time threshold (Tt) values of a commercial EasyNAT system, which is based on cross priming amplification (CPA) technology, and the cycle threshold (Ct) values of the Cobas z480 analyzer, which is based on a real-time fluorescence polymerase chain reaction (PCR) method, in the detection of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) from oropharyngeal swabs. Design and Methods: Data were retrospectively collected from a clinical laboratory between December 4, 2022 and July 1, 2024. ResultsA total of 277 EasyNAT-positive samples (Tt values from 3.83 to 29.5) were simultaneously investigated using the Cobas z480 analyzer (Ct values from 10.74 to 38.78). The concordance rate between the two systems was 100 %. Among the positive samples, the mean and maximum PCR Ct values of O and N genes increased in line with increasing Tt values of the left and right amplification areas of the EasyNAT system. The maximum Ct values of the O or N gene determined by the Cobas z480 analyzer were no more than 29.52 when the Tt values of the left or right amplification areas of the UC0116 analyzer were no more than 6. ConclusionsThe safe, simple, fast, accurate, and automatic EasyNAT system used in conjunction with a PCR system might be a better choice for the detection of SARS-CoV-2 in hospitals, especially in settings without sophisticated PCR facilities. The Tt value (≤6) of the EasyNAT system can be a reference index for estimating the maximum Ct value (29.52) in SARS-CoV-2-positive samples.

Automatic batching compound fertilizer production system based on parallel bin structure

Automatic batching compound fertilizer production system based on parallel bin structure