Field Of Control Research Articles

Pattern formations and their active manipulation in a Rydberg noisy-dressed Bose–Einstein condensate

We investigate the formation and manipulation of spatial patterns and their structural phase transitions by examining the effects of laser linewidth on the dynamics of Rydberg noise-dressed Bose–Einstein condensates (RnD BECs). We discover that the homogeneous matter wave can transition into various types of self-organized patterns, which are manipulated by tuning the laser linewidth, control field intensity, and atomic density. Remarkably, the system exhibits stable nonlocal matter-wave solitons, vortices, and soliton molecules under specific laser linewidths.

What motivates the choice to custom hire pest management spraying services?

AbstractBACKGROUNDThis article presents a model of how farmers choose to custom hire for pest control. The decision‐making process is illustrated through a discrete choice experiment conducted via a pilot survey of soybean growers in Michigan, Illinois, and Indiana. Farmers responded to a hypothetical pest infestation by choosing between custom operators, spraying on their own, or leaving the field to its fate.RESULTSAmong farmers who choose to spray, the mean willingness to pay for marginal increases in timeliness (as defined as the chance of late spraying) ranges from 37 to 52 cents per acre. We also find that farmers more averse to risk are more sensitive to custom operator timeliness and that farmers with better‐developed social networks are less sensitive to the risk of delay.CONCLUSIONThe results of this study can motivate future research into the drivers of on‐farm decision‐making, especially as it relates to custom hire behavior in pest control and other field operations. © 2024 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Effect of alternate wetting and drying technique (AWD) on water productivity of paddy in major irrigation schemes – A case study in Mahaweli System B

This report investigates the effectiveness of the Alternate Wetting and Drying (AWD) technique on water productivity and yield in paddy cultivation within Mahaweli System B, located in Sri Lanka's dry zone. With increasing water scarcity, particularly during the Yala season, farmers struggle to meet irrigation demands using traditional methods. The study compares AWD with conventional irrigation practices, focusing on its ability to reduce water consumption while maintaining or increasing rice yields. Two paddy fields were selected for trials, and the results show that fields using AWD consumed significantly less water, averaging 3.7 feet per acre, compared to 5.3 feet in conventionally irrigated fields. Moreover, AWD fields produced an average yield of 6.04 tons per hectare, an increase of over 100 kg compared to the control fields, which yielded 5.04 tons per hectare. The technique also reduced the frequency of irrigation events, offering a practical solution to water management challenges in the region. These findings indicate that AWD can enhance water productivity without sacrificing crop yield, making it a promising strategy for areas facing water scarcity. However, further studies across multiple seasons and varied locations are recommended to validate its long-term benefits and adaptability.

The application of Deep Learning in the field of Robotics

Abstract. As a new field with rapid development in the past two decades, deep learning has received more and more attention from researchers. Neural network adopts widely interconnected structure and effective learning mechanisms to simulate the process of information processing in the human brain, which is an important method in the development of artificial intelligence. Compared with shallow models, deep learning can achieve stronger unsupervised autonomous learning capabilities by increasing the number of layers of the network. In the past, the robots needed to be controlled by the humans; they controlled the robot to finish different tasks. In recent years, the researchers have tried to apply deep learning in the field of robots. Deep neural networks can simulate the complex cognitive laws of the human brain, so many researchers apply deep learning to robots to make robots have the thinking ability of humans. This article will review the cases of combining robot and in-depth learning in recent decades, Summarizing the achievements and problems faced in the three fields of robot vision, trajectory planning and motion control.

Discrete real-time learning of quantum-state subspace evolution of many-body systems in the presence of time-dependent control fields

Discrete real-time learning of quantum-state subspace evolution of many-body systems in the presence of time-dependent control fields

MODERNIZATION OF STATE POLICY IN THE FIELD OF STATE CONTROL (SUPERVISION) OVER ECONOMIC ACTIVITY

The article analyzes the essence of modernization of the State policy in the field of control (supervision) over economic activity with due regard for the changing political and economic situation in the country. The author examines the main conceptual approaches to the definition of basic terms, and also identifies the features and purpose of state control (supervision) in the economic sphere. It is found that the state of the system of control (supervision) over economic activity does not always correspond to the realities of today. Hence, the author concludes that the control system is not always relevant and effective. The author identifies the main problems on the way to modernization of legislation in the field of control (supervision) over economic activity. The author proposes to use adequate means of regulating and controlling economic activity during a special period caused, for example, by a pandemic, military operations on the territory of Ukraine, etc. The author examines the key areas of state policy in the field of legal regulation of control (supervision) over economic activity. The author defines the system of regulatory and legal support of the state policy in the field of control over economic activity at different stages of economic development of the country. The author analyzes the legal acts adopted under the legal regime of martial law aimed at stabilizing the situation in the economic system of our country.

Focal volume optics for composite structuring in transparent solids

Abstract Achieving high-level integration of composite micro-nano structures with different structural characteristics through a minimalist and universal process has long been the goal pursued by advanced manufacturing research but is rarely explored due to the absence of instructive mechanisms. Here, we revealed a controllable ultrafast laser-induced focal volume light field and experimentally succeeded in highly efficient one-step composite structuring in multiple transparent solids. A pair of spatially coupled twin periodic structures reflecting light distribution in the focal volume are simultaneously created and independently tuned by engineering ultrafast laser-matter interaction. We demonstrated that the generated composite micro-nano structures are applicable to multi-dimensional information integration, nonlinear diffractive elements, and multi-functional optical modulation. This work presents the experimental verification of highly universal all-optical fabrication of composite micro-nano structures with independent controllability in multiple degrees of freedom, expands the current cognition of ultrafast laser-based material modification in transparent solids, and establishes a new scientific aspect of strong-field optics, namely, focal volume optics for composite structuring transparent solids.

The Best Paper Award 2024 Congratulations!

The 15th Best Paper Award 2024 ceremony was held at Gakushikaikan, Tokyo, Japan, on September 20, 2024, attended by the winners and IJAT Editorial Committee members. The Best Paper was severely selected from among 58 papers published in Vol.17 (2023). The Best Paper Award winner received a certificate along with an honorarium of JPY100,000 (nearly US$1,000). We extend our heartfelt congratulations to the winners and sincerely wish them continued success in their future endeavors. The 15th Best Paper Award Thitipat Permpatdechakul, Panart Khajornrungruang, Keisuke Suzuki, and Shotaro Kutomi Study on a Novel Peeling of Nano-Particle (PNP) Process for Localized Material Removal on a 4H-SiC Surface by Controllable Magnetic Field Int. J. of Automation Technology, Vol.17 No.4 pp. 410-421, 2023

Generation and enhancement of sum sideband in a magnon Kerr nonlinearity assisted optomechanical system

Abstract A theoretical scheme to enhance the sum sideband generation (SSG) via magnon Kerr nonlinearity assisted optomechanical system is proposed. In this scheme, the yttrium iron garnet sphere is placed within the cavity system and the frequency components are generated at the sum sideband through optomechanical nonlinear interaction and cavity-magnon linear coupling interaction. The results show that the efficiency of SSG can be enhanced by several orders of magnitude, and the gain in SSG efficiency also varies. The dependence of SSG on the system parameters, including the power of the control field, the frequency detuning of the probe fields and the coupling strengths between the optomechanical coupling and the cavity-magnon coupling is analyzed in detail. The change of SSG by varying the optomechanical coupling strength and cavity-magnon coupling strength is also investigated, and it is found that new matching conditions are generated. The enhanced SSG method may have potential application prospects in realizing the measurement of high-precision weak forces, quantum information processing and quantum-sensitive sensing.

The use of skylark plots by the European Skylark (Alauda arvensis) in Germany

AbstractThe Eurasian Skylark is still undergoing a strong population decline. A simple and cheap measure to provide support are bare patches in winter cereal fields (“skylark plots”). Previous studies showed mixed evidence about their effectiveness. In this study, over 7 years, a total of 68 fields in Germany with skylark plots were monitored. Fields with skylark plots had significantly higher densities of Eurasian Skylark sightings compared to control fields (median 15%), but only on 50% of farms. Crop diversity within 500 m radius was the only consistent factor in the best models to explain the variability in effectiveness. Due to their low costs and high potential effectiveness, we recommend a wide implementation of skylark plots.

APPLICATION OF ARTIFICIAL INTELLIGENCE TECHNIQUES FOR ERROR PREVENTION AND QUALITY CONTROL IN MIG/MAG WELDING PROCESSES: A COMPREHENSIVE REVIEW

Welding techniques, particularly MIG/MAG (Metal Inert Gas/Metal Active Gas) processes, are essential for various industries, including automotive, construction, aerospace, and defense. Ensuring the quality and accuracy of welds is crucial for efficient production and product reliability. However, numerous issues can arise during MIG/MAG welding, often resulting in suboptimal quality. This study presents a comprehensive review of research efforts employing AI techniques to address errors and defects in MIG/MAG welding. The review systematically analyzes relevant studies published since 2018, focusing on three key aspects: datasets employed, methodologies and approaches adopted, and performance metrics reported. The findings reveal a significant adoption of both machine learning and deep learning techniques, with the choice of approach dependent on factors such as the nature of input data, welding process dynamics, and computational requirements. Deep learning models, particularly convolutional neural networks (CNNs) and long short-term memory (LSTM) networks, have demonstrated superior performance in tasks like image-based defect detection and time-series analysis for quality prediction. However, traditional machine learning algorithms have also been utilized, often in conjunction with dimensionality reduction or feature selection techniques. The review highlights the diverse range of performance metrics employed, including accuracy, precision, recall, F1-score, mean squared error (MSE), and root mean squared error (RMSE), with the selection contingent upon the specific task (classification or regression) and desired trade-off between different performance aspects. While many studies have reported promising results, with accuracy rates frequently exceeding 90%, challenges remain in real-world industrial settings, where factors such as noise, occlusions, and rapidly changing welding conditions can pose significant hurdles. This review serves as a comprehensive guide for researchers and practitioners working in the field of AI-assisted error prevention and quality control for MIG/MAG welding processes, highlighting current trends, methodologies, and future research directions.

The Application of PLC in Industry Fields

This article explores the widespread application and importance of the Programmable Logic Controller (PLC) in industry. PLC, as an industrial controller designed specifically for industrial environments, occupies an important position in the field of industrial automation control due to its advantages of being less susceptible to interference, high reliability, easy programming, fast installation, and small size. With the rapid development of PLC technology, great progress has been made in the development of technology, hardware, and software, resulting in increasingly powerful functionalities and significantly enhanced system development and compatibility. This paper mainly analyzes the design ideas and applications of PLC in life and industry in detail, aiming to research PLC and find more scenes in industry fields in which PLC can participate. PLC has a wide range of applications and significant importance in industry. The continuous progress and innovation of its technology will bring more opportunities and challenges to the field of industrial automation control. In the future, with the deepening development of advanced manufacturing models such as Industry 4.0 and intelligent manufacturing, PLC technology is expected to play a greater role in more fields and promote industrial automation to a higher level.

Automatic control strategy of electronic and electrical engineering based on FPGA

Field Programmable Gate Array (FPGA) have demonstrated significant potential in the field of automation control due to their flexibility, programmability, and high performance. This study designs an FPGA-based automation control strategy for motor control systems, encompassing four core modules: signal acquisition, signal processing, control algorithm, and output drive. The signal acquisition module employs the AD9280 high-speed, high-precision ADC chip to achieve rapid and accurate signal acquisition. The signal processing module utilizes digital filtering and FFT analysis within the FPGA to extract key information such as motor speed. The control algorithm module adopts an adaptive fuzzy control strategy that fine-tunes control rules in real-time to ensure precise control. The output drive module generates PWM signals via the FPGA to drive the motor, guaranteeing efficient and stable operation. Experimental results indicate that the FPGA-based control strategy significantly outperforms traditional methods in terms of response speed and stability, capable of meeting the high-performance requirements of modern industrial motor control systems. This research provides new technical insights and practical references for the field of automation control in electrical and electronic engineering.

Deep Learning and Human-machine Integration in Smart Prosthetic Control: Process and Perspectives

With the rapid development of science and technology and the maturity of deep learning technology, intelligent prosthetic limb control has made significant progress in human-machine integration. While traditional prosthetic technology has seen improvements in form and function, it still faces challenges in user experience and physiological adaptability. Deep learning, with its powerful pattern recognition and decision-making capabilities, offers new possibilities to address these issues. This paper reviews the current status and future development of the application of deep learning in intelligent prosthetic limb control, emphasizing its close relationship with the concept of human-machine integration. Intelligent prosthetic control involves not only mechanical engineering and bioengineering, but also interdisciplinary integration of the fields of neural engineering, electrical engineering, motion control and computer science. This paper reviews the limitations in traditional prosthetic technology, such as accuracy and user adaptability, introduces the successful cases and latest research results of deep learning in the medical field, and explores the potential of deep reinforcement learning in optimizing complex movements and adapting to different environments. Finally, the future direction of deep learning technology in smart prosthetic limb control is envisioned, and research challenges and recommendations are presented in the hope of providing theoretical support for the innovative development of smart prosthetic limb technology and improving the quality of life of people with disabilities.

Optimization Analysis of Low-Noise Amplifier

This paper mainly analyzes the important component of a wireless receiver – low-noise amplifiers (LNA). Low-noise amplifiers can reduce the effect of noise on the received signal and amplify signals. For the better development of wireless communication technology, remote control, and other related fields, it is necessary to optimize the design of low-noise amplifiers, so that low-noise operational amplifiers can finally obtain high gain, low noise figure, and other advantages. This paper analyzes the optimization design of LNA in the field of Global Navigation Satellite Systems (GNSS). This paper analyzes a low-noise amplifier design with the operation of concurrent dual-band for GNSS receivers with a single channel. The optimized design of a low-noise amplifier in this field uses a low-cost 0.18µm CMOS tube and adds load capacitances and a feedforward path to reduce the noise figure (NF) of the system. Noise figures in 1.2 GHz and 1.57 GHz bands are reduced by about 0.9 dB. In addition, the high gain, high linearity, and other excellent properties are shown in 1.2 GHz and 1.57GHz. In the application of 5G/6G network technology, the optimized design of Gallium Arsenide (GaAs) PHEMT technology with a gate length of 0.3µmm and inductively degraded common source topology phase structure is adopted. From this optimization, the noise figure is optimized to 1.3-1.4, and the gain of the system is 20-22 dB. At the same time, good linearity is also shown. Then, the prospects of semiconductor materials such as Gallium Nitride (GaN) and Indium Phosphide (InP), which have the advantages of high electron mobility and low-cost design, in optimizing low noise operational amplifiers. To a certain extent, the in-depth study of the optimal design of LNA can improve the technical level of wireless communication, aerospace, and other fields.

The Supervising Role of the Apron Movement Control (AMC) Unit on Aviation Security and Safety at Pattimura Ambon International Airport

Security and safety are crucial factors in aviation activities, considering the sensitivity of air transportation that requires assurance of safety at all times. The success of the AMC unit's tasks and responsibilities is measured by their ability to optimize supervision, thus creating safe and secure conditions, in accordance with applicable regulations. This study aims to evaluate the role of the AMC unit in ensuring security and safety in the airside area of Pattimura Ambon International Airport and to identify obstacles in supervision in the area. The approach used in this study is descriptive qualitative. The data collected consists of primary and secondary data. Primary data is obtained through observation and interviews, while secondary data comes from literature studies and photographs related to the problem being studied. Data analysis techniques involve data reduction, data presentation, and drawing conclusions. To ensure the validity of the data, triangulation techniques are used. The research was conducted in March 2024. The results of the study indicate that the AMC unit at Pattimura Ambon International Airport has carried out supervision well in accordance with the standard operating procedures PM-IK (Quality Procedures and Work Instructions). Supervision covers four components of the work area: Airport Operation Control Center (AOCC), Data Entry, Field Inspection, and Aviobridge Operations. Supervision is carried out through inspections every two hours for FOD and fuel spills, supervision of aircraft movements and engine running up/idle, GSE vehicle speed, and worker compliance with the use of Personal Protective Equipment. The AMC unit strives to implement the 3S+1C principle (Safety, Security, Service, and Compliance). The obstacles faced include a shortage of personnel, which causes an increase in workload and less than optimal supervision, as well as violations by service users or workers in the airside area, which have the potential to cause accidents.

Evaluation of in-house-built pipette-tip micro-solid-phase extraction devices for sample preparation in the analysis of amino compounds by liquid chromatography-tandem mass spectrometry

Amino compounds are of significant interest in dietary, clinical, and quality control fields. Efficient extraction is crucial for comprehensive metabolomics, especially for amino acids and biogenic amines, but traditional solid-phase extraction (SPE) methods are costly and require large solvent volumes. Miniaturized SPE techniques, like pipette-tip micro-solid-phase extraction (PT-µ-SPE), offer promising alternatives by improving throughput and reducing solvent and sorbent usage. This study presents PT-µ-SPE for the screening and quantification of amino compounds in bee products, particularly honey. The method involves derivatization with diethyl ethoxymethylenemalonate (DEEMM) and analysis using liquid chromatography-triple quadrupole mass spectrometry. Silica-based SCX sorbents were effective for a broad range of amino compounds, while WCX sorbents were better for aliphatic amines. The method's extraction efficiency was assessed across sample loading, washing, and elution solution, with recovery rates of 70 - 120% in oat bran, sea buckthorn leaves, and honey extracts. Matrix effects were observed for four amino compounds in honey. Limits of detection (LoD) and quantification (LoQ) ranged from 0.37 to 57 µg L⁻¹ and 1.13 to 174 µg L⁻¹, respectively. Covering 48 amino compounds under different PT-µ-SPE conditions, this method has been applied to several samples, demonstrating accuracy, environmental sustainability, cost-effectiveness, portability, and versatility in amino compound analysis.

A gamma-ray stacking survey of Fermi-LAT undetected globular clusters

ABSTRACT We present evidence for $\gamma$-ray emission from a stacked population of 39 high-latitude globular clusters (GCs) not detected in the Fermi Point Source Catalogue, likely attributable to populations of millisecond pulsars within them. In this work, we use 13 yr of data collected by the Large Area Telescope aboard the Fermi Gamma-Ray Space Telescope to search for a cumulative signal from undetected GCs and compared them to control fields (CFs), selected to match the celestial distribution of the target clusters so as to distinguish the $\gamma$-ray signal from background emission. The joint likelihood distribution of the GCs has a significant separation ($\sim 4\sigma$) from that of the CFs. We also investigate correlations between detected cluster luminosities and other cluster properties such as distance, the number of millisecond pulsars associated with each cluster, and stellar encounter rate but find no significant relationships.

Superposition of standing waves induced ultra high-resolution atom localization

Abstract In this study, we have theoretically demonstrated ultra-high resolution two-dimensional atom localization within a three-level $\lambda$-type atomic medium via superposition of asymmetric and symmetric standing wave fields. Our analysis provides understanding into the precise spatial localization of atomic positions at the atomic level, utilizing advanced theoretical approaches and principles of quantum mechanics. The dynamical behavior of a three-level atomic system is thoroughly analyzed using the density matrix formalism within the realm of quantum mechanics. A theoretical approach is constructed to describe the interaction between the system and external fields, specifically a control field and a probe field. The absorption spectrum of the probe field is thoroughly examined to clarify the spatial
localization of the atom within the proposed configuration. We have theoretically investigated that symmetric and asymmetric superposition phenomena significantly influence the localized peaks within a two-dimensional spatial domain. Specifically, the emergence of one and two sharp localized peaks has been observed within a region of one wavelength domain. We observed notable influences of the intensity of the control field, probe field detuning, and decay rates on atom localization. Ultimately, we have achieved an unprecedented level of ultra-high resolution and precision in localizing an atom within an area smaller than λ/35×λ/35. These findings hold promise for potential applications in domains such as Bose-Einstein condensation, nanolithography, laser cooling, trapping of neutral atoms, and the measurement of center-of-mass wave-functions.

Research on the Friction Force Characteristics for the Double O-ring Seal of the Cylinder under the Small Displacement Condition

In order to obtain a high-precision pneumatic control system, it is necessary to study the friction force of the cylinder. However, few have considered the cylinder's frictional characteristics at small-displacements. This study investigated the influence of different conditions on the cylinder friction characteristics during the process from static to small-displacement of pneumatic double O-ring seal. A set of experimental apparatuses controlled by an electric actuator perform a seal ring small-displacement friction test to achieve the goals. The working principle of sealing rings in different deformation stages is expounded. According to experiments, the sealing ring's friction force in small-displacement movement can be separated into tilt, elastic deformation, pre-sliding, and sliding friction stages. Furthermore, the clearance characteristics between the sealing ring and the piston groove are verified, which decreases with the sealing ring thickness. Finally, the friction displacement characteristics of sealing rings under different pressures and materials during the elastic deformation stage were verified. It can be concluded that when the displacement is between 0.05-0.25mm, the friction of the sealing ring is almost linear with the displacement; when the displacement reaches 0.25mm, with the increase of the displacement, the friction force changes in a similar parabola manner. This study provides a detailed analysis of the friction characteristics of the seal in different stages of small displacement, which plays an important reference role in overcoming cylinder friction and promotes the development of pneumatic systems in the field of accurate position and speed control.