Статті в журналах з теми "Intelligent Instrumentaion"

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1

Harper, A. M., and S. A. Liebman. "Intelligent instrumentation." Journal of Research of the National Bureau of Standards 90, no. 6 (November 1985): 453. http://dx.doi.org/10.6028/jres.090.041.

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2

Preece, C. "Intelligent Instrumentation." Electronics and Power 32, no. 3 (1986): 233. http://dx.doi.org/10.1049/ep.1986.0148.

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3

Clarke, D. W. "Intelligent instrumentation." Transactions of the Institute of Measurement and Control 22, no. 1 (March 2000): 3–27. http://dx.doi.org/10.1177/014233120002200102.

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4

Howell, S. K., and T. D. S. Hamilton. "Intelligent instrumentation." Measurement Science and Technology 1, no. 12 (December 1, 1990): 1265–73. http://dx.doi.org/10.1088/0957-0233/1/12/001.

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5

Clarke, D. W. "Intelligent instrumentation." Transactions of the Institute of Measurement and Control 22, no. 1 (January 1, 2000): 3–27. http://dx.doi.org/10.1191/014233100675191926.

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6

Jakuš, Vladimír. "Artificial Intelligence in Chemistry." Collection of Czechoslovak Chemical Communications 57, no. 12 (1992): 2413–51. http://dx.doi.org/10.1135/cccc19922413.

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Анотація:
The definition of artificial intelligence and the associated tasks of this branch of science are discussed. The tasks include pattern recognition, adaptation and learning, problem solving by means of expert systems or neural networks, and understanding the natural language and communication with a machine in it. The principles of problem solving are analyzed. It is demonstrated how artificial intelligence-based computer programs in which chemical expertise is encoded assist in structure elucidation, in the investigation of relations between structure and biological activity or chromatographic retention, etc.; problems emerging in the synthesis planning with a retrosynthetic analysis, or in the planning of experiments and intelligent consultations are dealt with. Several models used for structure elucidation and synthesis planning are evaluated. An overview is presented of additional expert systems which, along with artificial intelligence-based robotics, are used in intelligent instrumentation. Also discussed is the role of neural networks, which begin to be successfully employed in structure elucidation, synthesis planning, in intelligent instrumentation and in the treatment of natural languages. They are expected to be an important tool in the implementation of intelligent systems for the classification of chemical databases and prediction of properties of molecules.
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7

Beckman, R. J. "Intelligent instrumentation - Discussion." Journal of Research of the National Bureau of Standards 90, no. 6 (November 1985): 464. http://dx.doi.org/10.6028/jres.090.042.

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8

Kohoutek, H. J. "Intelligent instrumentation: a quality challenge." ACTA IMEKO 3, no. 1 (May 7, 2014): 47. http://dx.doi.org/10.21014/acta_imeko.v3i1.195.

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Анотація:
<p>This is a reissue of a paper which appeared in ACTA IMEKO 1988, Proceedings of the 11th Triennial World Congress of the International Measurement Confederation (IMEKO), "Instrumentation for the 21st century", 16.-21.10.1988, Houston, pp. 337-345.</p><p>After a review and description of current trends in the design of electronic measurement and analytical instrumentation, changes in its application and use, and of associated quality issues, this paper deals with new quality issues emerging from the expected increase of artificial intelligence impact on system design and implementation strategies. The concept of knowledge quality in all its aspects (i.e. knowledge levels, representation, storage, and processing) is identified as the key new issue. Discussion of crucial knowledge quality attributes and associated assurance strategies suggests the need to enrich the assurance sciences and technologies by the methods and tools of applied epistemology. Described results from current research and investigation, together with first applications of artificial intelligence to particular analytical instruments, lead to conclusion that the conceptual framework of quality management is, in general, adequate for successful resolution of all quality issues associated with intelligent instrumentation.</p>
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9

Boettcher, J., and H. R. Traenkler. "Trends in Intelligent Instrumentation." IFAC Proceedings Volumes 22, no. 18 (November 1989): 241–48. http://dx.doi.org/10.1016/s1474-6670(17)52849-9.

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10

Yadova, N., and S. Osiko. "Artificial Intelligence: Application and Development Prospects on the Example of Rocket and Space Instrumentation." Scientific Research and Development. Economics of the Firm 11, no. 2 (July 12, 2022): 54–59. http://dx.doi.org/10.12737/2306-627x-2022-11-2-54-59.

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Анотація:
The presented article deals with the implementation of artificial intelligence technologies in the instrument-making industry. The statistics of the use of systems with elements of artificial intelligence are analyzed. It presents the problems of legal regulation of artificial intelligence systems in the Russian Federation. In this regard, the purpose of the article is, on the one hand, to give the reader some information on state of intelligent systems in rocket and space instrumentation in the Russian Federation, and on the other hand, to identify the most promising areas of development in this area.
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11

Grabowski, D., U. Scherff, and R. Kötteritzsch. "Präzisionsmeßtechnik mit Intelligenz/ Intelligent precision measurement technology." teme 56, JG (December 1989): 341–47. http://dx.doi.org/10.1524/teme.1989.56.jg.341.

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12

Taner, A. H., and J. E. Brignell. "Virtual instrumentation and intelligent sensors." Sensors and Actuators A: Physical 61, no. 1-3 (June 1997): 427–30. http://dx.doi.org/10.1016/s0924-4247(97)80300-7.

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13

Diamond, Dermot. "Chemical sensors and intelligent instrumentation." TrAC Trends in Analytical Chemistry 8, no. 2 (February 1989): 58–62. http://dx.doi.org/10.1016/0165-9936(89)87019-0.

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14

Gooberman, G. "Book Review: Intelligent Instrumentation, 2nd Ed." International Journal of Electrical Engineering Education 27, no. 2 (April 1990): 166. http://dx.doi.org/10.1177/002072099002700213.

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15

Tortora, G. "Fault-tolerant control and intelligent instrumentation." Computing & Control Engineering Journal 13, no. 5 (October 1, 2002): 259–62. http://dx.doi.org/10.1049/cce:20020507.

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16

Long, Teng, Zhangbing Zhou, Gerhard Hancke, Yang Bai, and Qi Gao. "A Review of Artificial Intelligence Technologies in Mineral Identification: Classification and Visualization." Journal of Sensor and Actuator Networks 11, no. 3 (August 29, 2022): 50. http://dx.doi.org/10.3390/jsan11030050.

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Анотація:
Artificial intelligence is a branch of computer science that attempts to understand the essence of intelligence and produce a new intelligent machine capable of responding in a manner similar to human intelligence. Research in this area includes robotics, language recognition, image identification, natural language processing, and expert systems. In recent years, the availability of large datasets, the development of effective algorithms, and access to powerful computers have led to unprecedented success in artificial intelligence. This powerful tool has been used in numerous scientific and engineering fields including mineral identification. This paper summarizes the methods and techniques of artificial intelligence applied to intelligent mineral identification based on research, classifying the methods and techniques as artificial neural networks, machine learning, and deep learning. On this basis, visualization analysis is conducted for mineral identification of artificial intelligence from field development paths, research hot spots, and keywords detection, respectively. In the end, based on trend analysis and keyword analysis, we propose possible future research directions for intelligent mineral identification.
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17

Yu, Shu Fang, Xiao Ping Shi, and Xiu Liang Huang. "Intelligent Monitoring Design and Research of Modern Instrumentation Failure Alarm." Applied Mechanics and Materials 214 (November 2012): 534–37. http://dx.doi.org/10.4028/www.scientific.net/amm.214.534.

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Анотація:
The instrumentation is a complexity of the whole system composed by many circuit modules. In order to achieve the detection to the entire system, when the overall system design, the designer must design circuits with judge and test methods suitable for a variety of levels in the case of considering to enables various modules carry on the wrong judgment and state test. This will provide the capabilities of intelligent monitoring and detection for the normal operation of the whole system. This paper has briefly introduced the development trends of modern instrumentation, analyzed the classification level of the failure alarm, given the general intelligent failure alarm circuit and self-test circuit, and provided a theoretical basis and practical reference for the studying of intelligent design of the failure alarm in a variety of instrumentation.
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18

Chen, Liang-Chia. "Technological advances in measurements and intelligent instrumentation." Measurement Science and Technology 28, no. 5 (March 16, 2017): 050101. http://dx.doi.org/10.1088/1361-6501/aa6182.

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19

Kortela, U., and Y. Majanne. "Intelligent instrumentation of solid fuel power plants." IEEE Control Systems Magazine 7, no. 4 (August 1987): 31–35. http://dx.doi.org/10.1109/mcs.1987.1105332.

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20

Zhou, Dongdong, Ke Xu, Zhimin Lv, Jianhong Yang, Min Li, Fei He, and Gang Xu. "Intelligent Manufacturing Technology in the Steel Industry of China: A Review." Sensors 22, no. 21 (October 26, 2022): 8194. http://dx.doi.org/10.3390/s22218194.

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Анотація:
Intelligent manufacturing, defined as the integration of manufacturing with modern information technologies such as 5G, digitalization, networking, and intelligence, has grown in popularity as a means of boosting the productivity, intelligence, and flexibility of traditional manufacturing processes. The steel industry is a necessary support for modern life and economic development, and the Chinese steel industry’s capacity has expanded to roughly half of global production. However, the Chinese steel industry is now confronted with high labor costs, massive carbon emissions, a low level of intelligence, low production efficiency, and unstable quality control. Therefore, China’s steel industry has launched several large-scale intelligent manufacturing initiatives to improve production efficiency, product quality, manual labor intensity, and employee working conditions. Unfortunately, there is no comprehensive overview of intelligent manufacturing in China’s steel industry. We began this research by summarizing the construction goals and overall framework for intelligent manufacturing of the steel industry in China. Following that, we offered a brief review of intelligent manufacturing for China’s steel industry, as well as descriptions of two typical intelligent manufacturing models. Finally, some major technologies employed for intelligent production in China’s steel industry were introduced. This research not only helps to comprehend the development model, essential technologies, and construction techniques of intelligent manufacturing in China’s steel industry, but it also provides vital inspiration for the manufacturing industry’s digital and intelligence updates and quality improvement.
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21

Wang, Biyao, Yi Han, Di Tian, and Tian Guan. "Sensor-Based Environmental Perception Technology for Intelligent Vehicles." Journal of Sensors 2021 (September 2, 2021): 1–14. http://dx.doi.org/10.1155/2021/8199361.

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Environmental perception technology is the basis and premise of intelligent vehicle decision control of intelligent vehicles, a crucial link of intelligent vehicles to realize intelligence, and also the basic guarantee of its safety and intelligence. The accuracy and robustness of the perception algorithm will directly affect or even determine the realization of the upper function of intelligent vehicles. The wrong environmental perception will affect the control of the vehicle, thus causing safety risks. This paper discusses the intelligent vehicle perception technology and introduces the development status and control strategies of several important sensors such as machine vision, laser radar, and millimeter-wave radar. Target detection, target recognition, and multisensor fusion are analyzed in the optimized part of sensor results. The functions of the intelligent vehicle assistance system which has been applied to the ground at present are described, and the lane detection, adaptive cruise control (ACC), and autonomous emergency braking (AEB) are analyzed. Finally, the paper looks forward to the research direction of sense-based intelligent vehicle perception technology, which will play an important role in guiding the development of intelligent vehicles and accelerate the landing process of intelligent vehicles.
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22

Liu, Zongwei, Wang Zhang, Hong Tan, and Fuquan Zhao. "Feature Identification, Solution Disassembly and Cost Comparison of Intelligent Driving under Different Technical Routes." Applied Sciences 13, no. 7 (March 29, 2023): 4361. http://dx.doi.org/10.3390/app13074361.

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Technical route decision making of intelligent driving has always been the focus of attention of automotive enterprises and even the industry. Firstly, this study combs the main technical routes of intelligent driving at different levels from three dimensions: development strategy, intelligence allocation and sensor combination. Then, the methodology of technical component combination is designed to disassemble different technical routes into corresponding technical component combinations. Finally, an improved evaluation model of total cost of ownership of intelligent driving is developed and the total cost of ownership of intelligent driving system under different technical routes is compared. For the development strategy, even if the function superposition can follow some research and development achievements of low-level intelligent driving, scenario-driven is still the option with lower cost and better sustainability. For intelligence allocation, collaborative intelligence can effectively reduce the cost of the vehicle compared with single-vehicle intelligence by up to 46%, but the cost reduction depends on the original on-board hardware. For sensor combination, the multi-source fusion always has the cost advantage compared with vision-only, but the advantage is more obvious in the medium-level and high-level stage of single-vehicle intelligence.
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23

Timmerman, B. H., and P. J. Bryanston-Cross. "Intelligent optical diagnostic instrumentation for combustion and medicine." Computing & Control Engineering Journal 13, no. 5 (October 1, 2002): 231–36. http://dx.doi.org/10.1049/cce:20020502.

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24

Shan, De Shan, Peng Yan, and Zhen Hua Wang. "Intelligent Health Monitoring System for a Railway Cable-Stayed Bridge." Advanced Materials Research 148-149 (October 2010): 1390–93. http://dx.doi.org/10.4028/www.scientific.net/amr.148-149.1390.

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Анотація:
Intelligent health monitoring system of the long-span railway cable-stayed bridge requires the comprehensive knowledge of instrumentation, analytical and information processing technologies with the knowledge and experiences in design, construction, operation and maintenance of railway cable-stayed bridge for long-term monitoring the performance throughout its lifecycle. It is necessary to perform sensor-based structural monitoring for identifying the bridge conditions in order to assure the structural safety and to evaluate the operational performance. The considerations for deploying a proper monitoring system are appropriate sensor instrumentation, robust signal acquisition, reliable signal processing, and intelligent signal and information processing. The experience on developing an autonomous monitoring system in the one certain railway cable-stayed bridge newly constructed is introduced in this paper. Sensor and hardware instrumentation, signal transmission, signal acquisition and analysis are schematically described mainly. Experience through this work will be worthwhile lessons for other similar efforts.
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25

Saghiri, Ali Mohammad, S. Mehdi Vahidipour, Mohammad Reza Jabbarpour, Mehdi Sookhak, and Agostino Forestiero. "A Survey of Artificial Intelligence Challenges: Analyzing the Definitions, Relationships, and Evolutions." Applied Sciences 12, no. 8 (April 17, 2022): 4054. http://dx.doi.org/10.3390/app12084054.

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Анотація:
In recent years, artificial intelligence has had a tremendous impact on every field, and several definitions of its different types have been provided. In the literature, most articles focus on the extraordinary capabilities of artificial intelligence. Recently, some challenges such as security, safety, fairness, robustness, and energy consumption have been reported during the development of intelligent systems. As the usage of intelligent systems increases, the number of new challenges increases. Obviously, during the evolution of artificial narrow intelligence to artificial super intelligence, the viewpoint on the challenges such as security will be changed. In addition, the recent development of human-level intelligence cannot appropriately happen without considering whole challenges in designing intelligent systems. Considering the mentioned situation, no study in the literature summarizes the challenges in designing artificial intelligence. In this paper, a review of the challenges is presented. Then, some important research questions about the future dynamism of challenges and their relationships are answered.
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26

Wu, Suzhen. "Design of Intelligent Nursing System Based on Artificial Intelligence." Journal of Sensors 2022 (August 21, 2022): 1–5. http://dx.doi.org/10.1155/2022/7427968.

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Анотація:
As the number of the elderly population and the population dependency ratio increase year by year, the issue of old-age care has become the focus. However, due to the shortage of carers and the large-scale and expensive auxiliary equipment for the elderly, it is difficult to give thoughtful care to all the elderly. In view of the above background, this paper designs a set of intelligent nursing system for the elderly based on artificial intelligence (AI) algorithms, which mainly includes sensor terminals and AI processing algorithms. Among them, the sensor terminal mainly includes two parts: video monitoring and human biological signal monitoring. For video surveillance signals, this paper uses scene event detection algorithm to detect abnormal events, so as to automatically perceive possible unexpected situations. For human biological signals, such as heart rate, blood pressure, and pulse, the abnormal detection is carried out through data analysis and comparison with the normal index range. So, the possible problems in the physical state of the elderly can be judged in time. Through more comprehensive state monitoring and reliable algorithm processing, the system can effectively solve many hidden dangers in the current elderly care and provide a feasible solution for smart nursing.
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27

Naghshvarianjahromi, Mahdi, Shiva Kumar, and Mohammed Jamal Deen. "Natural Intelligence as the Brain of Intelligent Systems." Sensors 23, no. 5 (March 6, 2023): 2859. http://dx.doi.org/10.3390/s23052859.

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Анотація:
This article discusses the concept and applications of cognitive dynamic systems (CDS), which are a type of intelligent system inspired by the brain. There are two branches of CDS, one for linear and Gaussian environments (LGEs), such as cognitive radio and cognitive radar, and another one for non-Gaussian and nonlinear environments (NGNLEs), such as cyber processing in smart systems. Both branches use the same principle, called the perception action cycle (PAC), to make decisions. The focus of this review is on the applications of CDS, including cognitive radios, cognitive radar, cognitive control, cyber security, self-driving cars, and smart grids for LGEs. For NGNLEs, the article reviews the use of CDS in smart e-healthcare applications and software-defined optical communication systems (SDOCS), such as smart fiber optic links. The results of implementing CDS in these systems are very promising, with improved accuracy, performance, and lower computational costs. For example, CDS implementation in cognitive radars achieved a range estimation error that is as good as 0.47 (m) and a velocity estimation error of 3.30 (m/s), outperforming traditional active radars. Similarly, CDS implementation in smart fiber optic links improved the quality factor by 7 dB and the maximum achievable data rate by 43% compared to those of other mitigation techniques.
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28

Chi, Duan, Wang Zhi, Hao Luo, Feng Li, and Lianzhong Sun. "Embedded AI system for interactive vision screen based on human action recognition." Review of Scientific Instruments 93, no. 5 (May 1, 2022): 054104. http://dx.doi.org/10.1063/5.0076398.

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Анотація:
In recent years, vision screening has emerged globally for employment (on a yearly basis) within primary and high schools since myopia heavily affects school-aged children. However, this is a laborious and time-consuming task. This article proposes an intelligent system for “self-service” vision screening. Individuals can accomplish this task independently—without any assistance by technical staff. The technical solution involved within this platform is human action recognition realized by pose estimation (real-time human joint localization in images, including detection, association, and tracking). The developed system is based on a compact and embedded artificial intelligence platform, aided by a red–green–blue-D sensor for ranging and pose extraction. A set of intuitive upper-limb actions was designed for unambiguous recognition and interaction. The deployment of this intelligent system brings great convenience for large-scale and rapid vision screening. Implementation details were extensively described, and the experimental results demonstrated efficiency for the proposed technique.
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29

Oduoza, C. F., P. R. Fielden, and R. M. Miller. "Design of an intelligent electrochemical system using cybernetic instrumentation." Laboratory Automation & Information Management 32, no. 2-3 (November 1996): 71–85. http://dx.doi.org/10.1016/s1381-141x(96)00005-6.

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30

Jazayeri-Rad, H., and M. A. Browne. "Intelligent instrumentation for selective pulse excitation in NMR imaging." Journal of Physics E: Scientific Instruments 20, no. 6 (June 1987): 643–48. http://dx.doi.org/10.1088/0022-3735/20/6/014.

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31

Ullah, Muhammad Nasir, and Craig S. Levin. "Application of Artificial Intelligence in PET Instrumentation." PET Clinics 17, no. 1 (January 2022): 175–82. http://dx.doi.org/10.1016/j.cpet.2021.09.011.

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32

Wang, Wenli. "Research on the Architecture of Digital Song and Dance Costume Design System Based on Intelligent Deep Learning Algorithm." Journal of Sensors 2022 (February 7, 2022): 1–10. http://dx.doi.org/10.1155/2022/1545334.

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Анотація:
In order to improve the intelligence and reliability of song and dance costume design, this article combines the intelligent deep learning algorithm to improve the digital costume design process. In order to solve the problem of minimizing the energy of image deformation, this paper proposes to transform it into a sparse matrix to solve the problem, which is solved by constructing a coefficient matrix and multiple iterations. After the algorithm is improved, this article combines the digital intelligence method to construct the digital song and dance costume design system structure based on the intelligent deep learning algorithm and analyzes its work flow. Finally, this paper verifies the method in this paper through feasibility analysis and system performance test. From the experimental results, it can be seen that the digital song and dance costume design system based on the intelligent deep learning algorithm proposed in this article has a good effect in the song and dance costume design.
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33

Sensors, Journal of. "Retracted: Design of Intelligent Nursing System Based on Artificial Intelligence." Journal of Sensors 2023 (August 9, 2023): 1. http://dx.doi.org/10.1155/2023/9872157.

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34

Fu, Jie, Qiya Gao, and Shuang Li. "Application of Intelligent Medical Sensing Technology." Biosensors 13, no. 8 (August 13, 2023): 812. http://dx.doi.org/10.3390/bios13080812.

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Анотація:
With the popularization of intelligent sensing and the improvement of modern medical technology, intelligent medical sensing technology has emerged as the times require. This technology combines basic disciplines such as physics, mathematics, and materials with modern technologies such as semiconductors, integrated circuits, and artificial intelligence, and has become one of the most promising in the medical field. The core of intelligent medical sensor technology is to make existing medical sensors intelligent, portable, and wearable with full consideration of ergonomics and sensor power consumption issues in order to conform to the current trends in cloud medicine, personalized medicine, and health monitoring. With the development of automation and intelligence in measurement and control systems, it is required that sensors have high accuracy, reliability, and stability, as well as certain data processing capabilities, self-checking, self-calibration, and self-compensation, while traditional medical sensors cannot meet such requirements. In addition, to manufacture high-performance sensors, it is also difficult to improve the material process alone, and it is necessary to combine computer technology with sensor technology to make up for its performance shortcomings. Intelligent medical sensing technology combines medical sensors with microprocessors to produce powerful intelligent medical sensors. Based on the original sensor functions, intelligent medical sensors also have functions such as self-compensation, self-calibration, self-diagnosis, numerical processing, two-way communication, information storage, and digital output. This review focuses on the application of intelligent medical sensing technology in biomedical sensing detection from three aspects: physical sensor, chemical sensor, and biosensor.
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35

Furness, R. A. "Developments in Pipeline Instrumentation." Measurement and Control 20, no. 1 (February 1987): 7–17. http://dx.doi.org/10.1177/002029408702000102.

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Анотація:
Pipelines are an integral part of the world's economy and literally billions of pounds worth of fluids are moved each year in pipelines of varying lengths and diameters. As the cost of some of these fluids and the price of moving them has increased, so the need to measure the flows more accurately and control and operate the line more effectively has arisen. Instrumentation and control equipment has developed steadily in the past decade but not as fast as the computers and microprocessors that are now a part of most large scale pipeline systems. It is the interfacing of the new generation of digital and sometimes ‘intelligent’ instrumentation with smaller and more powerful computers that has led to a quiet but rapid revolution in pipeline monitoring and control. This paper looks at the more significant developments from the many that have appeared in the past few years and attempts to project future trends in the industry for the next decade.
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36

Jiao, Jingjie, Lixing Zhao, Wenhao Pan, and Xiaoyan Li. "Development and Core Technologies for Intelligent SWaP3 Infrared Cameras: A Comprehensive Review and Analysis." Sensors 23, no. 9 (April 22, 2023): 4189. http://dx.doi.org/10.3390/s23094189.

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Анотація:
With the development of infrared detection and imaging technology, infrared cameras (IRCs) play an important role in many fields, such as military, industry, and civilian. Additionally, the requirements for the size, performance, and intelligence of IRCs are becoming more and more strict. Consequently, the associated research and development (R&D) of IRCs is gradually focused on the aspects of miniaturization, high performance, intelligence, low power consumption, and low cost, involving many frontier fields, including artificial intelligence, new materials, new optical systems, and electronics systems. In fact, there are continual studies on intelligent SWaP3 IRCs, but unfortunately, a systematic arrangement and analysis are lacking. Therefore, a systematical and comprehensive review for the developments and core technologies of the intelligent SWaP3 IRCs is really needed. In this paper, in terms of the aforementioned requirements, we conduct a review and analysis of current intelligent SWaP3 IRCs based on 90 literature and statistics in recent decades to provide the relevant developers with a helpful reference for facilitating the indicator optimization of intelligent SWaP3 IRCs with new developed technologies. We analyze the development of SWaP3 IRCs in the aspects of lightweight, miniaturization, low price, and high performance, including hyperspectral resolution, high spatial resolution, large field of view (FOV), and wide dynamic elaborately. Moreover, the development in low power consumption and intelligence is also discussed in detail. Additionally, we briefly summarize the primary applications of intelligent SWaP3 IRCs in military, scientific, and civil. Then, the core technologies comprising high-integration, lightweight, hyperspectral imaging (HSI), low-power consumption, as well as the realization of high performance such as high-resolution, high-frame, and wide-dynamic range of SWaP3 IRCs are discussed and analyzed in detail. Finally, we prospect for the intelligent SWaP3 IRCs that it is necessary to continuously expand the concept of SWaP3 by reliability, stability, extensibility, and safety. In addition, it is useful to embed cutting-edge technologies such as small pixel pitch array, multi-sensors fusion, and deploy intelligent algorithms to IRCs. Additionally, the improvement of the whole machine from multi-dimension such as chip, camera, and system is expected and needs to be taken more seriously. It is hoped that this paper can provide a reference for the R&D of intelligent SWaP3 IRCs in the future.
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37

Yang, Liping, Joshua Driscol, Sarigai Sarigai, Qiusheng Wu, Christopher D. Lippitt, and Melinda Morgan. "Towards Synoptic Water Monitoring Systems: A Review of AI Methods for Automating Water Body Detection and Water Quality Monitoring Using Remote Sensing." Sensors 22, no. 6 (March 21, 2022): 2416. http://dx.doi.org/10.3390/s22062416.

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Water features (e.g., water quantity and water quality) are one of the most important environmental factors essential to improving climate-change resilience. Remote sensing (RS) technologies empowered by artificial intelligence (AI) have become one of the most demanded strategies to automating water information extraction and thus intelligent monitoring. In this article, we provide a systematic review of the literature that incorporates artificial intelligence and computer vision methods in the water resources sector with a focus on intelligent water body extraction and water quality detection and monitoring through remote sensing. Based on this review, the main challenges of leveraging AI and RS for intelligent water information extraction are discussed, and research priorities are identified. An interactive web application designed to allow readers to intuitively and dynamically review the relevant literature was also developed.
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38

Kong, Yuan, and A. P. Sakis Meliopoulos. "Intelligent merging unit: DSE-based online instrumentation channel error correction." Electric Power Systems Research 200 (November 2021): 107468. http://dx.doi.org/10.1016/j.epsr.2021.107468.

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39

Shaw, Brian M. "Book Review: Intelligent Instrumentation — Microprocessor Applications in Measurement and Control." International Journal of Electrical Engineering & Education 24, no. 1 (January 1987): 93. http://dx.doi.org/10.1177/002072098702400135.

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40

Sanderson, M. L. "Intelligent instrumentation—Microprocessor applications in measurement and control, 2nd Edn." Flow Measurement and Instrumentation 1, no. 1 (October 1989): 62. http://dx.doi.org/10.1016/0955-5986(89)90013-7.

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41

Finkelstein, L. "Intelligent and knowledge based instrumentation—An examination of basic concepts." Measurement 14, no. 1 (September 1994): 23–29. http://dx.doi.org/10.1016/0263-2241(94)90040-x.

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42

Zhang, Chenguang, and Kun Cheng. "Accurate Detection of Intelligent Running Posture Based on Artificial Intelligence Sensor." Journal of Sensors 2022 (July 16, 2022): 1–7. http://dx.doi.org/10.1155/2022/6561159.

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In order to solve the problem of low accuracy of human posture recognition during motion, the author proposes a human posture recognition and detection method based on multiple sensors. The method uses acceleration sensor, angular velocity sensor, and single-chip microcomputer to collect data; uses time domain and frequency domain analysis methods to analyze the collected data; and then uses Bayesian classifier to classify and identify the current motion posture of the human body. The obtained results are as follows: in the traditional method, with the increase of subjects, the accuracy of the classification method continues to decline; when the number of subjects reaches 50, the accuracy rate is only 60%; in the experiment, the zero crossing times of the acceleration signal axis are selected, and the axis area of the angular velocity signal is used as the characteristic item to distinguish the two different attitudes of going upstairs and going downstairs; the discrimination can reach about 90%. The authors combine the data collected by the acceleration sensor and the angular velocity sensor to perform feature extraction and classification, and the classification accuracy can reach more than 95%. It is proved that the method proposed by the authors can perform human gesture recognition very quickly and has a high accuracy rate.
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43

Lai, ZhiRong, Mingming Wang, Longhai Wang, and Yining Zhou. "Intelligent Running Posture Detection Based on Artificial Intelligence Combined with Sensor." Journal of Sensors 2022 (May 23, 2022): 1–7. http://dx.doi.org/10.1155/2022/6746260.

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In order to avoid injuries caused by incorrect running posture to a greater extent and reduce the impact on athletes’ performance and physical health, on the basis of artificial intelligence sensors, the author studies the accurate detection of intelligent running motion posture. Using artificial intelligence sensors, an adaptive error quaternion unscented Kalman filter (DAUKF) algorithm is designed. The attitude analysis and recognition system based on the inertial measurement unit can not only measure the motion information of human body but also obtain the motion characteristic data and movement state of the human body through the analysis of posture data. Use the error quaternion and gyroscope drift error to establish the equation of state, the measurement values of the accelerometer and magnetometer are used to establish the observation equation, and the fading memory method is introduced to adaptively adjust the observation noise covariance, so as to reduce the interference of the system itself and the environment on attitude detection. Experimental results show that the proposed method improves the attitude detection accuracy, effectively suppresses the influence of drift error and dynamic observation noise, and provides a foot attitude detection scheme suitable for long-distance running.
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44

Bond, Alan M., and Miroslav Švestka. "Developments, Trends and Commercial Availability of Instrumentation (Hardware and Software) in Microcomputer Based Voltammetry." Collection of Czechoslovak Chemical Communications 58, no. 12 (1993): 2769–812. http://dx.doi.org/10.1135/cccc19932769.

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Voltammetry is an important electrochemical technique which is used extensively to solve problems in many areas of chemistry. Since the method is based on the use of current-potential-time curves, voltammetric instrumentation is highly suited to computer based forms of technology. In this article, an overview of existing hardware and software that have been used to facilitate improvements in computer based voltammetric instrumentation is provided. it is concluded on the basis of this survey that developments to date in the use of computer based technology have been conservative relative to those in spectroscopic forms of instrumentation. Consequently, it is postulated that a new generation of more "intelligent" voltammetric instruments would become available immediately if the full power of presently available digital hardware and software were to be implemented as has been the case with some other forms of instrumentation.
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45

Kang, Sung-O., Eul-Bum Lee, and Hum-Kyung Baek. "A Digitization and Conversion Tool for Imaged Drawings to Intelligent Piping and Instrumentation Diagrams (P&ID)." Energies 12, no. 13 (July 5, 2019): 2593. http://dx.doi.org/10.3390/en12132593.

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In the Fourth Industrial Revolution, artificial intelligence technology and big data science are emerging rapidly. To apply these informational technologies to the engineering industries, it is essential to digitize the data that are currently archived in image or hard-copy format. For previously created design drawings, the consistency between the design products is reduced in the digitization process, and the accuracy and reliability of estimates of the equipment and materials by the digitized drawings are remarkably low. In this paper, we propose a method and system of automatically recognizing and extracting design information from imaged piping and instrumentation diagram (P&ID) drawings and automatically generating digitized drawings based on the extracted data by using digital image processing techniques such as template matching and sliding window method. First, the symbols are recognized by template matching and extracted from the imaged P&ID drawing and registered automatically in the database. Then, lines and text are recognized and extracted from in the imaged P&ID drawing using the sliding window method and aspect ratio calculation, respectively. The extracted symbols for equipment and lines are associated with the attributes of the closest text and are stored in the database in neutral format. It is mapped with the predefined intelligent P&ID information and transformed to commercial P&ID tool formats with the associated information stored. As illustrated through the validation case studies, the intelligent digitized drawings generated by the above automatic conversion system, the consistency of the design product is maintained, and the problems experienced with the traditional and manual P&ID input method by engineering companies, such as time consumption, missing items, and misspellings, are solved through the final fine-tune validation process.
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46

Zhu, Mingjiang. "Application of Moving Target Information Perception Technology in Intelligent Supervision System." Scanning 2022 (August 31, 2022): 1–7. http://dx.doi.org/10.1155/2022/5192601.

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In order to solve the problems of inaccurate information collection, incomplete information collection, and inconsistency of collected images in traditional sports injury collection methods, an application method of moving target information perception technology in intelligent supervision system is proposed. By judging and analyzing the potential motion damage posture of the motion posture intelligent tracking images, the collected motion intelligence tracking images are judged. The intelligent tracking image matrix can make up for the shortcomings of traditional images that are not connected, complete the identification, detect potential damage in time, and take targeted preventive measures and means. Finally, according to the target detection algorithm and target tracking algorithm, combined with OpenCV computer vision library and QT image library, an intelligent video surveillance target tracking simulation system is developed. The algorithm studied in this paper is to realize the target tracking function of the intelligent video surveillance system. Through the comparison of experimental results, the design method can accurately collect damage attitude information, without calculating continuous values, and the use of three-dimensional images in the positioning process can analyze the damage attitude from multiple angles.
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47

Yeom, Seokwon. "Special Issue on Intelligent Processing on Image and Optical Information II." Applied Sciences 13, no. 15 (August 2, 2023): 8896. http://dx.doi.org/10.3390/app13158896.

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48

Chen, Xi, Ao Yu, Ning Cai, Saite Wei, and Yongqing Tong. "Diagnostic Value of Specialist Systems in Sports Knee Injuries." Scanning 2022 (August 31, 2022): 1–7. http://dx.doi.org/10.1155/2022/1892877.

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In order to explore the diagnostic effect of the expert system in knee sports injury, a method of diagnostic value of expert system in sports knee sports injury is proposed. This paper mainly takes 200 professional football players in sports higher vocational colleges as the research object. There are 146 male athletes and 44 female athletes; we establish a football injury ontology knowledge base and use a reasoning engine to build an intelligent expert system diagnosis system, allowing users to quickly discover diseases, accurately diagnose injuries, and obtain the best means of rehabilitation. Through the investigation, it can be seen that the body parts caused by football injuries are more complex, and the types of injuries in each part are also different. Therefore, it is particularly important to establish an intelligent retrieval system with convenient query and clear diagnosis by the expert system. With the birth and development of computer and artificial intelligence technology, the development of artificial intelligence expert systems in the medical field has become a reality. The construction of this system will have theoretical and practical significance and application value.
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49

Yeom, Seokwon. "Special Issue on Intelligent Processing on Image and Optical Information III." Applied Sciences 13, no. 15 (August 2, 2023): 8898. http://dx.doi.org/10.3390/app13158898.

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50

Pan, Cao, Hui Ding, and Hong Yuan Wang. "The Research and Design of Instrument Management System Based on Wireless HART Technology." Applied Mechanics and Materials 241-244 (December 2012): 2350–53. http://dx.doi.org/10.4028/www.scientific.net/amm.241-244.2350.

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This paper presents a design of instrument management systems based on the wireless HART communications technology. The whole system achieves data of intelligent HART instrumentation uploading and setting through the wireless HART communication network. Data server software parses the data according to the wireless HART data frame format, and saves data through the real-time historical database of SCADA software Force Control 6.1. Application server provides a visual user interface, completes the configuration and monitoring for the field intelligent instrument and operates easily. This system has the scalability, reconfigurability, and other characteristics and it has a certain application value on the HART intelligent instruments of information management.
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