Hasil untuk "Automation"

M. Groover

R. Kodali, Vishal Jain, S. Bose et al.

Xiaobo Zhang, Zhongcai Pei, Zhiyong Tang

This paper presents a novel variable stiffness mechanism, namely the SBTDTS (Spinal Biomimetic Two-Dimensional Tensegrity Structure), which is constructed by integrating bioinspiration derived from biological spinal structures with the T-Bar mechanical design within tensegrity structures. A method for determining the torsional stiffness of the SBTDTS around a virtual rotational center is established based on parallel mechanism theory. The relationship between various structural parameters is analyzed through multiple sets of typical parameter combinations. Ultimately, the PSO (Particle Swarm Optimization) algorithm is employed to identify the optimal combination of structural parameters for maximizing the stiffness ratio, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>K</mi></mrow><mrow><mi>θ</mi><mo>_</mo><mi>t</mi><mi>i</mi><mi>m</mi><mi>e</mi></mrow></msub></mrow></semantics></math></inline-formula>, of SBTDTS under different constraint conditions. This optimal configuration is then compared with the RAPRPM (a type of rotational parallel mechanism) under different values of <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>μ</mi></mrow></semantics></math></inline-formula>, with an analysis of the distinct advantages of both variable stiffness structures.

Tengfei Song, Yu Liu, Xuefei Zhang et al.

About ten years ago, we established the first coronagraph that has been continuously operating on the high plateau of western China. This coronagraph is an internal occulting, 10 cm aperture instrument, installed at Lijiang Station through a collaboration with the Norikura Station of the National Astronomical Observatory of Japan. To ensure high efficiency in current and future coronal observations, developing integrated observation systems is essential for reliable, autonomous, and remote operation of coronagraphs. This paper introduces an advanced integrated observation and control system, based on the Lijiang 10 cm coronagraph. The coronagraph focuses on the observations for the solar inner corona, capturing the coronal green-line emission within a field range from <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>1.03</mn><msub><mi>R</mi><mo>⨀</mo></msub></mrow></semantics></math></inline-formula> to <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>2.5</mn><msub><mi>R</mi><mo>⨀</mo></msub></mrow></semantics></math></inline-formula>. To enhance the observational precision and efficiency, a comprehensive integrated system has been designed, incorporating various subsystems, including precise pointing and tracking mechanisms, a multi-band filter system, a protective dome system, and a robust data storage infrastructure. This paper details the hardware architecture and software frameworks supporting each subsystem. Results from extended operational testing confirm the stability of the system, its capacity for autonomous and remote observations, and significant improvements in the automation and efficiency of coronal imaging. The automated observation system will be further improved and used for our future coronagraphs to be developed for coronal magnetism diagnosis.

Pilar Ester Mariñoso, Presentación Ángeles Caballero García, Isabel Morales Jareño et al.

The use of Artificial Intelligence (AI) in Higher Education (HE) is an expanding reality, exerting an increasingly significant influence on teaching and learning processes. Its integration into the university environment is reshaping how instructors design and deliver their courses while providing students with new opportunities to personalize their learning experiences. Not only does AI enable task automation and resource optimization, but it also presents methodological, technological, and ethical challenges that warrant thorough investigation. In this context, we assessed the academic performance of two hundred and thirty eight students enrolled in an undergraduate degree program for early years education teachers, defining performance as their ability to design learning situations aimed at promoting mathematical thinking in young children. Our analysis distinguished between those who used AI to complete the task and those who relied on traditional teaching resources. To this end, we adopted a sequential explanatory mixed-methods design. In the quantitative phase, we employed a quasi-experimental post-test only design with experimental and control groups. In the qualitative phase, we conducted an in-depth analysis of the learning materials produced by the students in the experimental group with the support of AI. The findings indicate that the application of AI brought about significant changes in the teaching-learning process. The experimental group obtained better academic results than the control group. These results underscore, on one hand, the transformative potential of AI to improve pedagogical practices, and on the other, the need for research to examine its long-term effects on student learning, teacher engagement and ethical use, and the development of HE curricula that include AI as a teaching resource.

Yankai Li, Dongping Li, Fangqi Chen et al.

This paper considers a nonlinear impulsive fractional boundary value problem, which involves a <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>ψ</mi></semantics></math></inline-formula>-Caputo-type fractional derivative and integral. Combining critical point theory and fractional calculus properties, such as the semigroup laws, and relationships between the fractional integration and differentiation, new multiplicity results of infinitely many solutions are established depending on some simple algebraic conditions. Finally, examples are also presented, which show that Caputo-type fractional models can be more accurate by selecting different kernels for the fractional integral and derivative.

LIN Kaiping

Aiming at the situation of unstable control and high error during recoil compensation control of gunship borne automatic weapon, the recoil compensation control algorithm of gunship borne automatic weapon is proposed. According to the specific firing conditions of airborne automatic weapons, combined with the internal and external factors that affect the recoil of weapons, the force analysis is carried out. Meanwhile, the attitude parameters of gunship, including coordinate parameters and attitude Angle parameters, are calculated. On this basis, the control model of gunship is established, corresponding controller is designed, nonlinear interference observer is introduced, and adaptive control law is designed. The recoil compensation control of airborne automatic weapon is realized. The experimental results show that the proposed recoil compensation control algorithm has small control delay, can respond to compensation control changes in time, and has small control error. The overall fault tolerance of the control algorithm has been improved.

Kiselev Gennady G., Zolkin Alexander L., Bityutskiy Alexey S. et al.

The article discusses the need to improve the efficiency of freight cars operation by introducing modern technologies in the maintenance process. To improve the quality of technical inspection of rolling stock at the maintenance point, it is offered to introduce a robotic complex capable of autonomously conducting technical inspection and diagnostics of rolling stock. Structurally, the robotic complex includes: chassis; manipulator; automation, control and data transmission system; diagnostic equipment; power unit. The possibility of using various diagnostic tools, vision systems, non-contact scanning sensors is considered. The functions of the complex are to pass through the inspection positions, identify malfunctions, accumulate information about the technical condition of the car with the transfer of information to the fleet operator or maintenance point.

Mary C. Lacity, L. Willcocks

Siddharth Dadhich, Ulf Bodin, Ulf Andersson

A wheel loader is an earth-moving machine used in construction sites, gravel pits and mining to move blasted rock, soil and gravel. In the presence of a nearby dump truck, the wheel loader is said to be operating in a short loading cycle. This paper concerns the moving of material (soil, gravel and fragmented rock) by a wheel loader in a short loading cycle with more emphasis on the loading step. Due to the complexity of bucket-environment interactions, even three decades of research efforts towards automation of the bucket loading operation have not yet resulted in any fully autonomous system. This paper highlights the key challenges in automation and tele-remote operation of earth-moving machines and provides a survey of different areas of research within the scope of the earth-moving operation. The survey of publications presented in this paper is conducted with an aim to highlight the previous and ongoing research work in this field with an effort to strike a balance between recent and older publications. Another goal of the survey is to identify the research areas in which knowledge essential to automate the earth moving process is lagging behind. The paper concludes by identifying the knowledge gaps to give direction to future research in this field.

Aleksandre Asatiani, Esko Penttinen

Veronika Čabinová, Peter Gallo, Ján Dobrovič et al.

The paper's chief goal is to determine the impact of COVID-19 on consumer purchasing behaviour and purchasing decisions concerning selected factors affecting consumers when buying food products in chain stores. The research was conducted in V4 countries, and data were obtained from a questionnaire. Essential research methods, such as analysis, synthesis, comparison, induction and deduction, were used in the presented research. Selected basic methods of descriptive statistics, normality tests and correlation coefficients were also applied. After evaluating the results of the questionnaire and verifying the research hypotheses, the expected conclusion regarding the apparent impact of COVID-19 on consumer purchasing and decision-making was confirmed. The hypothesis focused on buying behaviour in relation to gender (p = 0.03665), and economic status (p = 0.0407) was confirmed, manifesting a statistically significant relationship between these factors. A statistically significant relationship between age and buying behaviour during the COVID-19 pandemic was not confirmed (p > 0.05). The research's benefit is identifying changes in buying behaviour and consumer decision-making during the COVID-19 pandemic, which is crucial information, especially for entrepreneurs who can thus adjust their business activities to the current customer needs.

Vikram E. Chhatre, Kevin J. Emerson

Population structure inference using the software STRUCTURE has become an integral part of population genetic studies covering a broad spectrum of taxa including humans. The ever-expanding size of genetic data sets poses computational challenges for this analysis. Although at least one tool currently implements parallel computing to reduce computational overload of this analysis, it does not fully automate the use of replicate STRUCTURE analysis runs required for downstream inference of optimal K. There is pressing need for a tool that can deploy population structure analysis on high performance computing clusters. We present an updated version of the popular Python program StrAuto, to streamline population structure analysis using parallel computing. StrAuto implements a pipeline that combines STRUCTURE analysis with the Evanno ΔK analysis and visualization of results using STRUCTURE HARVESTER. Using benchmarking tests, we demonstrate that StrAuto significantly reduces the computational time needed to perform iterative STRUCTURE analysis by distributing runs over two or more processors. StrAuto is the first tool to integrate STRUCTURE analysis with post-processing using a pipeline approach in addition to implementing parallel computation – a set up ideal for deployment on computing clusters. StrAuto is distributed under the GNU GPL (General Public License) and available to download from http://strauto.popgen.org.

Qitao Huang, Bowen Li, Hongguang Xu

Several studies have shown that actuation concepts such as Serial elastic actuator (SEA) can reduce peak power and energy consumption in ankle prostheses. Proper selection and design of the actuation concepts is important to unlock the power source potential. In this work, the optimization design, mechanical design, control scheme, and bench experiments of a new powered ankle–foot prosthesis is proposed. The actuation concept of this prosthesis is parallel elastic actuator (PEA) composed of electro-hydrostatic actuator (EHA) as the power kernel and a unidirectional parallel spring as the auxiliary energy storage element. After the appropriate motor and transmission ratio was selected, a dynamic model of the PEA prosthesis was built to obtain the appropriate spring parameters driven by biological data. The design of the hydraulic and mechanical system and the controller were provided for the implementation of the designed system. Bench experiments were performed to verify the performance. The results showed that the designed prosthesis meets the biomechanical dynamics requirements. This result emphasizes the feasibility of the EHA as a power source and actuator and provides new ideas for the design of ankle–foot prostheses.

Xuehua Wu, Qianqian Qian, Yuqing Bao

Demand response (DR) has a great potential for stabilizing the frequency of power systems. However, the performance is limited by the accuracy of the frequency detection, which is affected by measurement disturbances. To overcome this problem, this paper proposes a disturbance estimation-based Kalman filtering method, which is utilized for the frequency control. By using the rate of change of frequency (RoCoF), the Kalman filtering method can estimate the state of the ON/OFF loads well. In this way, the influence of detection error can be reduced, and the DR performance can be improved. Test results show that the proposed disturbance estimation-based Kalman filtering method has a higher accuracy of frequency detection than existing methods (such as the low-pass filter method) and therefore improves the frequency control performance of DR.

N. Yu. Kaufman, S. Yu. Zelentsova

The article explores the principles of building a competitive specialist in adigitally transformed economy, and presents the prerequisites that justify the development of staff training through the automation of HR technologies. The interpretation of the concepts «digital economy», «EdTech», «staff training», «gamification» is given. The main barriers preventing the implementation of HR Tech solutions in organisations are showed. The use of statistical analysis and comparison methods made it possible to present the areas of HR Tech, where digitalisation most actively improves and automates processes. It has been revealed that the main drivers of efficiency in the HR sphere can be modern tools and platforms that contribute to the introduction of automation in the personnel training system. The events of recent years have led to the understanding that it will no longer be possible to work effectively without the use of new technologies, therefore, the advantages of automating learning processes are highlighted. The role and area of responsibility of the training and development manager in the process of staff training has been established. Scenarios for solving the problem of a shortage of a digital specialist have been determined.

Takeshi Yoshida, Yuki Onishi, Takuya Kawahara et al.

Abstract In this study, we propose a method to automate fruit harvesting with a fruit harvesting robot equipped with robotic arms. Given the future growth of the world population, food shortages are expected to accelerate. Since much of Japan’s agriculture is dependent on imports, it is expected to be greatly affected by this upcoming food shortage. In recent years, the number of agricultural workers in Japan has been decreasing and the population is aging. As a result, there is a need to automate and reduce labor in agricultural work using agricultural machinery. In particular, fruit cultivation requires a lot of manual labor due to the variety of orchard conditions and tree shapes, causing mechanization and automation to lag behind. In this study, a dual-armed fruit harvesting robot was designed and fabricated to reach most of the fruits on joint V-shaped trellis that was cultivated and adjusted for the robot. To harvest the fruit, the fruit harvesting robot uses sensors and computer vision to detect and estimate the position of the fruit and then inserts end-effectors into the lower part of the fruit. During this process, there is a possibility of collision within the robot itself or with other fruits depending on the position of the fruit to be harvested. In this study, inverse kinematics and a fast path planning method using random sampling is used to harvest fruits with robot arms. This method makes it possible to control the robot arms without interfering with the fruit or the other robot arm by considering them as obstacles. Through experiments, this study showed that these methods can be used to detect pears and apples outdoors and automatically harvest them using the robot arms.

J. Delsing

J. Danaher

W. Jabbar, Mohammed Hayyan Alsibai, Nur Syaira S. Amran et al.

Home Automation System (HAS) gains popularity due to communication technology advancement. Smart home is one of the Internet of Things (IoT) applications that facilitates the control of home appliances over the Internet using automation system. This paper proposes a low-cost Wi-Fi based automation system for Smart Home (SH) in order to monitor and control home appliances remotely using Android-based application. An Arduino Mega microcontroller provided with Wi-Fi module is utilized to build the automation system. In addition, several sensors are used to monitor the temperature, humidity and motion in home. A relay board is exploited to connect the HAS with home under controlled appliances. The proposed automation system, can easily and efficiently control the electrical appliances via Wi-Fi and Virtuino mobile application.