Journal articles: 'Intelligent machine'

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Blanco Pérez, Carlos, and Eduardo Garrido-Merchán. "Do artificial intelligence systems understand?" Claridades. Revista de Filosofía 16, no. 1 (2024): 171–205. http://dx.doi.org/10.24310/crf.16.1.2024.16441.

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Are intelligent machines really intelligent? Is the underlying philosoph- ical concept of intelligence satisfactory for describing how the present systems work? Is understanding a necessary and sufficient condition for intelligence? If a machine could understand, should we attribute subjectivity to it? This paper addresses the problem of deciding whether the so-called ”intelligent machines” are capable of understanding, instead of merely processing signs. It deals with the relationship between syntax and semantics. The main thesis concerns the inevitability of semantics for any discussion about the possibility of building conscious machines, condensed into the following two tenets: ”If a machine is capable of understanding (in the strong sense), then it must be capable of combining rules and intuitions”; “If semantics cannot be reduced to syntax, then a machine cannot understand.” Our conclusion states that it is not necessary to attribute understanding to a machine in order to explain its exhibited “intelligent” behavior; a merely syntactic and mechanistic approach to intelligence as a task-solving tool suffices to justify the range of operations that it can display in the current state of technological development.

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Liu, Heng Li, and Tao Cheng. "Research on Multi-Physical Domain Information Fusion Method of Intelligent Processing Machine Based on GMM-HMM." Applied Mechanics and Materials 864 (April 2017): 184–91. http://dx.doi.org/10.4028/www.scientific.net/amm.864.184.

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As a typical unit of intelligent manufacturing system, intelligent processing machine is also a microcosm of Intelligent Manufacturing System (IMS), and the realization of intelligent manufacturing system will be firstly embodied in the intelligent processing machine as the core of intelligence. Therefore, it is inevitable to do a comprehensive and systematic study of intelligent processing machines and will get more and more attentions. In the study of intelligent machines, perceptual technology is an important part. Without effective perceptual technology, intelligent machines cannot interact with the environment, and thus the intelligence level cannot be improved. At present, the quite popular approach is to study the connection between perception and behavior from various simple behaviors and realize the higher intelligence through the combination of these behaviors on the basis of simple behaviors. The basis of autonomy perception of intelligent machines is to make it have the capability of multi-physical domain information fusion of manufacturing process and environment. An improved data processing and information fusion method based on GMM-HMM is proposed, which provides a self-perception of intelligent processing machines and a multi-physical domain information fusion method [1]. The simulation results show that the method proposed in this paper can realize the self - identification of intelligent processing machines in the intelligent manufacturing environment, such as the state of manufacturing, health and fault.

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Laszlo, Barna Iantovics, Gligor Adrian, A. Niazi Muaz, Iuliana Biro Anna, Miklos Szilagyi Sandor, and Tokody Daniel. "BRAIN. Broad Research in Artificial Intelligence and Neuroscience-Review of Recent Trends in Measuring the Computing Systems Intelligence." BRAIN. Broad Research in Artificial Intelligence and Neuroscience-Review of Recent Trends in Measuring the Computing Systems Intelligence 9, no. 2 (2018): 77–94. https://doi.org/10.5281/zenodo.1245893.

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Many difficult problems, from the philosophy of computation point of view, could require computing systems that have some kind of intelligence in order to be solved. Recently, we have seen a large number of artificial intelligent systems used in a number of scientific, technical and social domains. Usage of such an approach often has a focus on healthcare. These systems can provide solutions to a very large set of problems such as, but not limited to: elder patient care; medical diagnosis; medical decision support; out-of-hospital emergency care; drug classification among others. A recent key focus is that most of these developed intelligent systems are agent-based approaches, or in other words, they can be considered as agent-based intelligent systems (ABISs). ABISs are formally based on a set of interacting intelligent agents (IAs) in addition to the use of intelligent cooperative approaches namely forming intelligent cooperative multiagent systems (ICMASs). The main direction of study consists in the possibility to measure the artificial systems intelligence, frequently called machine intelligence quotient (MIQ). Recently, we performed some research related to the measuring of the machine intelligence. There is presented a comprehensive review of the scientific literature related to the measuring of the MIQ. We consider that the measuring of the machine intelligence is very actual and important, which could allow the differentiation of ABISs based on their intelligence, choosing of the agent-based systems able to solve the most intelligently specific problems. As the main conclusion of the performed study, we mention that cannot be given a unanimous definition of the ABISs intelligence. Even if the machine intelligence cannot be defined, it could be measured. We discuss this affirmation more in-depth in the paper. This is similar to the human intelligence that is not understood very well but can be measured using human intelligence tests.

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Ragg, C., T. Jungeblut, and B. Jurke. "Intelligente Werkzeugmaschinen/Intelligent tool machines." wt Werkstattstechnik online 105, no. 05 (2015): 252–56. http://dx.doi.org/10.37544/1436-4980-2015-05-4.

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Dieser Fachbeitrag beschreibt das optimierte Einrichten eines Bearbeitungsprozesses auf einer Werkzeugmaschine. Eine „intelligente“ Messtechnik erkennt die Spannsituation und bestimmt autonom den exakten Nullpunkt, gefolgt von einer realitätsnahen Simulation zum Validieren des auszuführenden NC-Programms. Dieser Ansatz steht im Fokus des Forschungsprojekts „Intelligente Werkzeugmaschine“ (iWZM) im Rahmen des Spitzenclusters „Intelligente Technische Systeme OstWestfalenLippe“ (it’s OWL). &nbsp; This technical paper describes an optimized set up of a machining process on a tool machine. An intelligent measuring method detects the clamping situation and determines autonomously the exact zero point followed by a realistic simulation that validates the NC program. This approach is focussed by the research project “Intelligent Machine Tool“ (iWZM), which is part of the government-financed project “Intelligent Technical Systems OstWestfalenLippe“ (it’s OWL).

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PAKKRATOKE, Montree, Tassanai SANPONPUT, Rugkanawan KONGKAVITUL, and Apichaya MEESAPLAK. "INT-08 DEVELOPMENT OF INTELLIGENT HARDNESS MEASUREMENT MACHINE(Intelligent Machines III,Technical Program of Oral Presentations)." Proceedings of JSME-IIP/ASME-ISPS Joint Conference on Micromechatronics for Information and Precision Equipment : IIP/ISPS joint MIPE 2009 (2009): 49–50. http://dx.doi.org/10.1299/jsmemipe.2009.49.

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Asif, Muhammad, Hang Shen, Chunlin Zhou, et al. "Recent Trends, Developments, and Emerging Technologies towards Sustainable Intelligent Machining: A Critical Review, Perspectives and Future Directions." Sustainability 15, no. 10 (2023): 8298. http://dx.doi.org/10.3390/su15108298.

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Intelligent manufacturing is considered among the most important elements of the modern industrial revolution, which includes digitalization, networking, and the development of the intelligent manufacturing industry. With the progressive development of modern information technology, particularly the new generation of artificial intelligence (AI) technology, many new opportunities are coming into existence for intelligent machine tool (IMT) development. Intelligent machine tools offer diverse advantages, including learning and optimizing machining processes, error compensation, energy savings, and failure prevention. The paper focuses on the machine tool market in terms of global production, the leading machine tool-producing countries, and the leading countries’ market share in machine tool production. Moreover, the usage of various artificial intelligence techniques in intelligent machining operations is also considered in this comprehensive review, including machining parameter optimization, tool condition monitoring (TCM), and chatter vibration management of intelligent machine tools. Furthermore, future challenges for the machine tool industry are also highlighted.

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Wu, Zhaohui, Gang Pan, Jose C. Principe, and Andrzej Cichocki. "Cyborg Intelligence: Towards Bio-Machine Intelligent Systems." IEEE Intelligent Systems 29, no. 6 (2014): 2–4. http://dx.doi.org/10.1109/mis.2014.94.

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Li, Tianran. "Research Perspective in Flexible Hand Exoskeleton." Highlights in Science, Engineering and Technology 39 (April 1, 2023): 334–38. http://dx.doi.org/10.54097/hset.v39i.6550.

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The purpose of writing this review paper is to make it more convenient for the public to use and adapt to hand exoskeletons, especially to enhance the promotion of flexible hand exoskeletons, and to put forward some of my own views. In recent years, a flexible exoskeleton human-machine intelligent system has become a new research hotspot in the fields of robotics, electromechanical engineering, automatic control, bioengineering and artificial intelligence, and has been widely used in scientific research, industrial production, space or deep-sea exploration, entertainment, etc. Sports rehabilitation and daily life have gradually been widely used. Flexible exoskeletons are most commonly used in the medical and biological fields. The human-machine intelligent technology of a flexible exoskeleton takes man-machine integration technology as the core, and the advantages of people and intelligent machines can be fully utilized. Through organic human-machine coupling, perception and decision-making at the execution level, the performance of the system is enhanced. Teleoperated exoskeletons and augmented exoskeletons are two important research directions for flexible exoskeleton human-machine intelligent systems.

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Kodgire, Dr Shilpa P., Ms K. Khandagle, Priyanka Nainav, and Shivprasad Gadekar. "Intelligent Google Assisted Coffee Vending Machine." Journal of Embedded Systems and Processing 7, no. 2 (2022): 9–14. http://dx.doi.org/10.46610/joesp.2022.v07i02.002.

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In rapidly growing smart world, all the vending machines must be smart and intelligent. Modern lifestyle which requires fast processing speed with high quality. The intelligent vending machines used worldwide have many latest technologies to make it smarter and more useful. The current trends of Internet of Things gave rise to eruption of sensor computing platform. The intricacy and uses of Interne of things devices make simple vending machine to interactive artificial intelligent and smart. Vending machines are also used to serves the beverage like cold drink, snacks and for ticketing purposes. Most of the Vending Machines are coin, RFID or manual switch operated. Here in the paper, we present vending machine not operated on currency or RFID, but it works with Voice command. This vending Machine can have access only through Voice which is given through the google assistant and mic.

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Davies, A. "The intelligent machine." Manufacturing Engineer 73, no. 4 (1994): 182–85. http://dx.doi.org/10.1049/me:19940402.

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Moriwaki, Toshimichi. "Intelligent Machine Tools." Journal of the Society of Mechanical Engineers 96, no. 901 (1993): 1010–14. http://dx.doi.org/10.1299/jsmemag.96.901_1010.

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Tung, Wei-Fung, and Soe-Tsyr Yuan. "Intelligent service machine." Communications of the ACM 53, no. 8 (2010): 129–34. http://dx.doi.org/10.1145/1787234.1787268.

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Botha, Anthon P. "A mind model for intelligent machine innovation using future thinking principles." Journal of Manufacturing Technology Management 30, no. 8 (2019): 1250–64. http://dx.doi.org/10.1108/jmtm-01-2018-0021.

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Purpose The purpose of this paper is to address the possible future evolution of innovation from a human-only initiative, to human–machine co-innovation, to autonomous machine innovation and to arrive at a conceptual mind model that outlines the role of innovation regimes and innovation agents. Design/methodology/approach This is a concept paper where a theoretical “thought experiment” is done, using future thinking principles and data that originate from the literature. Findings A conceptual mind model is developed to facilitate a better understanding of complexity at the edge of innovation where intelligent machines will emerge as innovators of the cyber world. It was found that innovation will gradually evolve from a human-only activity, to human–machine co-innovation, to incidences of autonomous machine innovation, based on the growth of machine intelligence and the adoption of human–machine partnership management models in future. Research limitations/implications Very little information is available in the literature on intelligent machines doing innovation. The work is based on a theoretical approach that presents new concepts to be debated, but have not been tested in engineering and technology management practice, except for a conference presentation and academic discussion. Practical implications The current world view is that future “smartness” is only possible through the creative abilities that humans have, but as machines are entering the workplace and our daily lives, not only as static robots on a manufacturing line, but as intelligent systems with the potential to replace lawyers and accountants, doctors and teachers, companions and partners, their role in innovation in complex environments needs to be explored. Social implications Human–machine interaction is often an emotional social issue of concern in terms of the replacement of human intelligence with machine intelligence. It should be asked whether humans will or should remain in control of innovation? Artificial intelligence (AI) may complement and even substitute human intelligence, but huge value is embedded in the new goods, services and innovations AI will enable, especially in manufacturing, where value embedded in the project becomes complex and dynamic. Originality/value The thinking presented in this paper is original and should lead to debate to question the way innovation systems will work in future and inspires thinking about AI and innovation.

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Zou, Yunhe, Jianxin Wu, Shijie Guo, Xiaojuan Song, and He Lyu. "The Exploration and Research of AI+ Intelligent Machine Vision in Practice Teaching." Journal of Higher Education Research 5, no. 2 (2024): 113. http://dx.doi.org/10.32629/jher.v5i2.2417.

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The rapid development and gradual perfection of artificial intelligence (AI) and intelligent machine vision technology have promoted the expansion of their application fields. And at this stage, AI+ intelligent machine vision has been widely used in practical teaching. Moreover, because artificial intelligence (AI) and intelligent machine vision technology involve many knowledge subjects, it is necessary to explore and study them effectively in order to give full play to their effectiveness in practical teaching.

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Zou, Guobin, Junwu Zhou, Tao Song, Jiawei Yang, and Kang Li. "Hierarchical Intelligent Control Method for Mineral Particle Size Based on Machine Learning." Minerals 13, no. 9 (2023): 1143. http://dx.doi.org/10.3390/min13091143.

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Mineral particle size is an important parameter in the mineral beneficiation process. In industrial processes, the grinding process produces pulp with qualified particle size for subsequent flotation processes. In this paper, a hierarchical intelligent control method for mineral particle size based on machine learning is proposed. In the machine learning layer, artificial intelligence technologies such as long and short memory neural networks (LSTM) and convolution neural networks (CNN) are used to solve the multi-source ore blending prediction and intelligent classification of dry and rainy season conditions, and then the ore-feeding intelligent expert control system and grinding process intelligent expert system are used to coordinate the production of semi-autogenous mill and Ball mill and Hydrocyclone (SAB) process and intelligently adjust the control parameters of DCS layer. This paper presents the practical application of the method in the SAB production process of an international mine to realize automation and intelligence. The process throughput is increased by 6.05%, the power consumption is reduced by 7.25%, and the annual economic benefit has been significantly improved.

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Shi, Rong Bo, Zhi Ping Guo, and Zhi Yong Song. "Research Based on State Monitoring of CNC Machine Tools Intelligent Security System." Applied Mechanics and Materials 427-429 (September 2013): 1328–32. http://dx.doi.org/10.4028/www.scientific.net/amm.427-429.1328.

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Analyse the cause of fault in CNC Machine, research the corresponding solve scheme, and to realize the state can monitor equipment operation, improve equipment reliability, the development set of machine condition monitoring, fault warning, fault diagnosis and troubleshooting as one of the intelligent security system. Based on the CNC machine intelligence support system research, design, introduces the key technologies and methods. Screw lift state of motion monitoring, for example, trend analysis exercise state, intelligent fault diagnosis, in order to achieve protection of the intelligent CNC machine tools to verify the practicality of intelligent security systems.

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Wang, Chen Sheng, Tjamme Wiegers, and Joris S. M. Vergeest. "An Implementation of Intelligent CNC Machine Tools." Applied Mechanics and Materials 44-47 (December 2010): 557–61. http://dx.doi.org/10.4028/www.scientific.net/amm.44-47.557.

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Improving the machining efficiency of CNC machine tools by introducing intelligence is now gaining more attention from both researchers and entrepreneurs. Based on the assessment of existing strategy of intelligent machine tool design, an implementation and preliminary evaluation of an intelligent CNC lathe has been reported in this paper. Techniques discussed in this paper are expected to benefit CNC machine tool researchers and designers in terms of the development of intelligent CNC machine tools.

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Bajpai ,, Suyash. "Intelligence Surveillance System Using Machine Learning." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 04 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem31165.

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The improvement of vision-based artificial intelligence, the rise of the Internet of Things connected cameras, and the increasing common need for rapid security, the demand for exact real-time intelligent surveillance has never been higher. For a human it is very difficult to monitor surveillance videos continually, so a smart and intelligent system is essential that can do real time monitoring of all activities and can categories between usual and some unusual activities. This paper aims to transform the surveillance landscape, to bring more effective, intelligent, and equitable security to the field, resulting in safer and more protected communities without requiring people to compromise their right to privacy. Keys—Surveillance, artificial intelligence, IOT, computer vision, application, real-world, real-time, edge,

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Wang, Yingxu, Fakhri Karray, Sam Kwong, et al. "On the philosophical, cognitive and mathematical foundations of symbiotic autonomous systems." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 379, no. 2207 (2021): 20200362. http://dx.doi.org/10.1098/rsta.2020.0362.

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Symbiotic autonomous systems (SAS) are advanced intelligent and cognitive systems that exhibit autonomous collective intelligence enabled by coherent symbiosis of human–machine interactions in hybrid societies. Basic research in the emerging field of SAS has triggered advanced general-AI technologies that either function without human intervention or synergize humans and intelligent machines in coherent cognitive systems. This work presents a theoretical framework of SAS underpinned by the latest advances in intelligence, cognition, computer, and system sciences. SAS are characterized by the composition of autonomous and symbiotic systems that adopt bio-brain-social-inspired and heterogeneously synergized structures and autonomous behaviours. This paper explores the cognitive and mathematical foundations of SAS. The challenges to seamless human–machine interactions in a hybrid environment are addressed. SAS-based collective intelligence is explored in order to augment human capability by autonomous machine intelligence towards the next generation of general AI, cognitive computers, and trustworthy mission-critical intelligent systems. Emerging paradigms and engineering applications of SAS are elaborated via autonomous knowledge learning systems that symbiotically work between humans and cognitive robots. This article is part of the theme issue ‘Towards symbiotic autonomous systems'.

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Thomas, Philip S., Bruno Castro da Silva, Andrew G. Barto, Stephen Giguere, Yuriy Brun, and Emma Brunskill. "Preventing undesirable behavior of intelligent machines." Science 366, no. 6468 (2019): 999–1004. http://dx.doi.org/10.1126/science.aag3311.

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Intelligent machines using machine learning algorithms are ubiquitous, ranging from simple data analysis and pattern recognition tools to complex systems that achieve superhuman performance on various tasks. Ensuring that they do not exhibit undesirable behavior—that they do not, for example, cause harm to humans—is therefore a pressing problem. We propose a general and flexible framework for designing machine learning algorithms. This framework simplifies the problem of specifying and regulating undesirable behavior. To show the viability of this framework, we used it to create machine learning algorithms that precluded the dangerous behavior caused by standard machine learning algorithms in our experiments. Our framework for designing machine learning algorithms simplifies the safe and responsible application of machine learning.

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Shukla, Prashant, H. James Wilson, Allan Alter, and David Lavieri. "Machine reengineering: robots and people working smarter together." Strategy & Leadership 45, no. 6 (2017): 50–54. http://dx.doi.org/10.1108/sl-09-2017-0089.

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Purpose The authors explore the potential of machine learning, computers employ that an algorithm to sort data, make decisions and then continuously assess and improve their functionality. They suggest that it be used to power a radical redesign of company processes that they call machine reengineering. Design/methodology/approach The authors interpret a survey of more than a thousand corporate public agency IT professionals on their use of artificial intelligence and machine learning. Findings Companies that embrace machine learning find that it adds value to the work product of their employees and provides companies with new capabilities. Practical implications Working together with an intelligent machine, workers become custodians of powerfully smart tools, tools that personalize work to maximize their most productive ways of working. Originality/value A guide to establishing a culture that empowers employees to thrive alongside intelligent machines.

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Becherer, Marius, Michael Zipperle, and Achim Karduck. "Intelligent Choice of Machine Learning Methods for Predictive Maintenance of Intelligent Machines." Computer Systems Science and Engineering 35, no. 2 (2020): 81–89. http://dx.doi.org/10.32604/csse.2020.35.081.

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Lenka, Dr Reena Mahapatra. "The impact of Emotional intelligence in the Digital Age." Psychology and Education Journal 58, no. 1 (2021): 1844–52. http://dx.doi.org/10.17762/pae.v58i1.1039.

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In today’s digital and automation obsessed world emotional intelligence is one important aspect which can differentiate a man from a machine. In this superbly technologically oriented world where most of us are crippled without a machine to help us it is a necessity for all of us to maintain our uniqueness in respect to machine. The uniqueness which differentiates us from a machine is our emotions towards different situations and people around us and how intelligently we handle these situations in a more human way. Simply put emotional intelligence is an aspect of human nature which helps all human being to understand themselves and others and try to overcome any problems or situations in a better way. Previously companies used to give more importance to IQ (Intelligent quotient) but now most of the companies are hiring those employees who are high on Emotional intelligence. The difference between intelligent quotient and emotional intelligence is that in intelligent quotient, people make smartdecisions irrespective of people’s feelings but in case of emotional intelligence, people make smart decisions by keeping people’s feelings in mind. The decision made by keeping in mind people’s feelings makes people happy and creates a happy and motivatedenvironment within the organization. Intelligent quotient is from birth but emotional intelligence depends on the environment we are born in and our surroundings and this can be changed according to the situation. In this digital age where the environment is constantly changing and full of challenges where people have stopped thinking about others feeling, emotional intelligence is the only way where people would start feeling a sense of belonginess, start being happy, relieved, motivated and start enjoying life to the fullest. This case study sheds light on the fact that emotional intelligence is very important in today’s automated world and also can also be a secret weapon which will help us survive and maintain our uniqueness before machine takes over human being in workplace.

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Te Chen, Ming. "A Secure Group Data Encryption Scheme in Intelligent Manufacturing Systems for IIoT." International Journal of Software Innovation 10, no. 1 (2022): 1–12. http://dx.doi.org/10.4018/ijsi.312577.

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In recent years, there are many industries that imported intelligent systems to help them make the intelligent factory and get product record analysis to evaluate product rate. These intelligent systems could generate product records, store them to the on-line database, and provide product rate analysis from these records. Due to the rapid development of internet of things (IoT), the stockholder can construct its own smart factory with the smart intelligent system to develop its own industrial internet of things (IIoT) architecture. With the help of IIoT, the smart intelligence system can collect data information with IoT sensors embedded into each machine in the production line. However, there are some security issues arising between smart intelligent systems and IoT devices. In addition, the authors also discovered that there are fewer methodologies to talk about the data security during the machine transmitting its censored data to the other machines under the same network environment.

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Rosemarie, Velik. "BRAIN Journal - Quo vadis, Intelligent Machine?" BRAIN - Broad Research in Artificial Intelligence and Neuroscience 1, no. 4 (2010): 13–22. https://doi.org/10.5281/zenodo.1037355.

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ABSTRACT Artificial Intelligence (AI) is a branch of computer science concerned with making computers behave like humans. At least this was the original idea. However, it turned out that this was no easy task to solve. This article aims to give a comprehensible review on the last 60 years of artificial intelligence taking a philosophical viewpoint. It is outlined what happened so far in AI, what is currently going on in this research area, and what can be expected in the future. The goal is to mediate an understanding for the developments and changes in thinking in the course of time about how to achieve machine intelligence. The clear message is that AI has to join forces with neuroscience and other brain disciplines in order to make a step towards the development of truly intelligent machines.

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Vieler, H., and A. Lechler. "Intelligente Schnittstellen für intelligente Werkzeuge/Intelligent interfaces for intelligent tools - Using intelligent tools with a unified interface in an easy way." wt Werkstattstechnik online 105, no. 07-08 (2015): 520–24. http://dx.doi.org/10.37544/1436-4980-2015-07-08-78.

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Um der geforderten Flexibilität in der Fertigungstechnik gerecht zu werden, kommen in Werkzeugmaschinen vermehrt intelligente Werkzeuge zur Anwendung. Hierfür sind mittlerweile diverse hersteller- und anwendungsspezifische Schnittstellen entstanden. Um den Einsatz dieser „smarten Tools“ zu vereinfachen, wird eine einheitliche Schnittstelle entwickelt. &nbsp; In order to fulfill the requested flexibility in manufacturing, an increasing number of intelligent tools is used in machine tools. To do so, diverse manufacturer and application dependent interfaces have been developed. To ease using these intelligent tools a unified interface is being developed.

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Wang, Zifan, Jianming Jian, Xiuying Tang, et al. "Intelligent residual film recovery machine monitoring and control system." Journal of Physics: Conference Series 2704, no. 1 (2024): 012021. http://dx.doi.org/10.1088/1742-6596/2704/1/012021.

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Abstract Domestic residue recovery machines in China still follow the traditional towed mechanical model, lacking automation and intelligent features. Under the key R&D project of Xinjiang Autonomous Region, our team has developed integrated intelligent agricultural machinery for cotton straw crushing and residue recovery. This research covers the monitoring and control system, including PLC control and communication, working parameter monitoring and adjustment, algorithmic control of electro-hydraulic actuators, and human-machine interface display. Compared to traditional models, this machine replaces the conventional chain-driven mechanical structure and diesel tractor traction power with a fully hydraulic integrated suspension drive and power system. Sensors, PLC, and a touch screen are utilized for real-time monitoring and display of parameters. Hardware components like electromagnetic switch valves, electro-hydraulic proportional valves, hydraulic cylinders, and software elements such as PLC programs and intelligent control algorithms are employed for electro-hydraulic switching and proportional control of certain working parameters and mechanisms. All parameter information is consolidated in the PLC host and expansion modules and displayed and controlled on the human-machine interface. The system was installed on the first-generation machine for indoor testing, revealing that the monitoring and control system used on the first-generation machine achieves parameter detection and adjustment of the actuating mechanisms. It incorporates more advanced functions compared to traditional residue recovery machines. However, there is still ample room for improvement in the overall intelligence of the machine. The control system’s structure requires adjustment, and certain functionalities of the overall mechanical structure and working components need optimization or upgrading. Detailed enhancements to the entire system will be made in the next-generation machine.

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Liu, Zhenghao, and Xi Zeng. "Hybrid Intelligence in Big Data Environment: Concepts, Architectures, and Applications of Intelligent Service." Data and Information Management 5, no. 2 (2021): 262–76. http://dx.doi.org/10.2478/dim-2020-0051.

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Abstract Based on the emerging concept of “Hybrid Intelligence,” this paper aims to explore a new model of human–computer interaction, and deeply research on its development and application of Intelligent Service in the big data environment. It systematically explores the related academic concepts of hybrid intelligence, and establishes its architecture model. The development of hybrid intelligence is faced with cognitive differences, system fragmentation, human–machine digital divide, and other issues. Strengthening the interaction between cognition and perception can be the key to break through the bottleneck. The intelligent service system based on the hybrid intelligent architecture takes knowledge fusion as the core, and “cloud intelligent brain” is making it possible for the human–computer symbiosis driven by hybrid intelligence. The proposed advanced human–computer interaction mode constructs a hybrid intelligent architecture model, enriches the concept system of human–machine hybrid intelligence, and provides a new landing scheme for intelligent services based on complex scenes in the big data environment.

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Wyatt, Ray. "An intelligent planning machine." Computers, Environment and Urban Systems 15, no. 3 (1991): 203–14. http://dx.doi.org/10.1016/0198-9715(91)90009-3.

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Chen, Jihong, Pengcheng Hu, Huicheng Zhou, et al. "Toward Intelligent Machine Tool." Engineering 5, no. 4 (2019): 679–90. http://dx.doi.org/10.1016/j.eng.2019.07.018.

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Musser, George. "A Truly Intelligent Machine." Scientific American 330, no. 4 (2024): 31. http://dx.doi.org/10.1038/scientificamerican0424-31.

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Schlechtendahl, J., S. Braun, P. Schraml, et al. "Modellbasierte, energieoptimale Maschinensteuerung*/Model-based, energy-optimal production control - Reduction of energy consumption over multiple layers within the control hierarchy." wt Werkstattstechnik online 105, no. 06 (2015): 440–44. http://dx.doi.org/10.37544/1436-4980-2015-06-92.

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Der Einfluss moderner Werkzeugmaschinen auf die Umwelt basiert größtenteils auf deren Energieverbrauch im Produktivbetrieb. Um diesen Energieverbrauch zu senken, bietet sich der Einsatz von modellbasierten Strategien an. Für die Nutzung dieser Strategien in Werkzeugmaschinensteuerungen müssen modellbasierte Optimierer und Steuerungsinformationen zur intelligenten Energieverbrauchssteuerung verknüpft werden. In diesem Fachbeitrag wird ein Ansatz für eine intelligente Energieverbrauchssteuerung vorgestellt sowie anhand von Prozess- und Komponentenoptimierern validiert. Teil 1 des Fachbeitrags ist erschienen in der wt-Ausgabe 5-2015 auf den Seiten 324–328. &nbsp; Modern machine tools mainly affect the environment by their energy consumption during operational life. Model-based strategies could be used for decreasing the energy consumption of machine tools. To enable the use of these strategies in machine controls, model-based optimizers and control information need to be connected to an intelligent energy controller. This paper introduces an approach to an intelligent energy controller for machine tools, validated by process and component optimizers.

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Qi, Kailong. "Intelligent Steward The Definition of Intelligent Machine Assistant and the Chronological Method of Intelligent Era Machine." Journal of Physics: Conference Series 1684 (November 2020): 012035. http://dx.doi.org/10.1088/1742-6596/1684/1/012035.

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Thoutam, Vivek. "Genetic Algorithms and Developments of Intelligent Machines." International Journal of Research and Applications 7, no. 28 (2020): 1801–7. https://doi.org/10.5281/zenodo.13341415.

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<strong>ABSTRACT</strong>Artificial intelligence is the study as well as progressions of smart devices and also a program that can rationalize, discover, gather knowhow, interact, man oeuvre as well as recognize the objects. John McCarthy created the term in 1956 as the limb of computer technology concerned with creating computers act like human beings. It is the research study of the estimation that makes it achievable to identify the reason and act. Artificial intelligence is different coming from psychological science given that, it is emphasis on estimation and also is different from computer technology due to its importance on viewpoint, thinking as well as activity. It helps make machines smarter and more useful.<strong>Keywords: </strong>Artificial intelligence, intelligent machine, machine learning. 

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Lawrence-Archer, Alex. "AI ETHICS: A STRATEGIC COMMUNICATIONS CHALLENGE." Defence Strategic Communications, no. 8 (July 3, 2020): 189–202. http://dx.doi.org/10.30966/10.30966/2018.riga.8.6.

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A Review Essay by Alex Lawrence-Archer AI Narratives: A History of Imaginative Thinking about Intelligent Machines Stephen Cave, Kanta Dihal, and Sarah Dillon (eds). Oxford University Press, 2020. Rage Inside the Machine: The Prejudice of Algorithms, and How to Stop the Internet Making Bigots of Us All Robert Elliot Smith. Bloomsbury Business, 2019. Keywords—strategic communication, strategic communications, AI, artificial intelligence, applied ethics, data science, machine learning

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Gao, Fei, Xiaojun Ge, Jinyu Li, Yuze Fan, Yun Li, and Rui Zhao. "Intelligent Cockpits for Connected Vehicles: Taxonomy, Architecture, Interaction Technologies, and Future Directions." Sensors 24, no. 16 (2024): 5172. http://dx.doi.org/10.3390/s24165172.

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Highly integrated information sharing among people, vehicles, roads, and cloud systems, along with the rapid development of autonomous driving technologies, has spurred the evolution of automobiles from simple “transportation tools” to interconnected “intelligent systems”. The intelligent cockpit is a comprehensive application space for various new technologies in intelligent vehicles, encompassing the domains of driving control, riding comfort, and infotainment. It provides drivers and passengers with safety, comfort, and pleasant driving experiences, serving as the gateway for traditional automobile manufacturing to upgrade towards an intelligent automotive industry ecosystem. This is the optimal convergence point for the intelligence, connectivity, electrification, and sharing of automobiles. Currently, the form, functions, and interaction methods of the intelligent cockpit are gradually changing, transitioning from the traditional “human adapts to the vehicle” viewpoint to the “vehicle adapts to human”, and evolving towards a future of natural interactive services where “humans and vehicles mutually adapt”. This article reviews the definitions, intelligence levels, functional domains, and technical frameworks of intelligent automotive cockpits. Additionally, combining the core mechanisms of human–machine interactions in intelligent cockpits, this article proposes an intelligent-cockpit human–machine interaction process and summarizes the current state of key technologies in intelligent-cockpit human–machine interactions. Lastly, this article analyzes the current challenges faced in the field of intelligent cockpits and forecasts future trends in intelligent cockpit technologies.

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Jiang, Yizhang, and Bo Li. "Exploration on the Teaching Reform Measure for Machine Learning Course System of Artificial Intelligence Specialty." Scientific Programming 2021 (November 30, 2021): 1–9. http://dx.doi.org/10.1155/2021/8971588.

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Due to the particularity of the artificial intelligence major and the machine learning courses learned, the traditional course teaching model is not suitable for artificial intelligence major machine learning courses. Based on this background, this article proposes a new system based on machine learning curriculum teaching reform. It mainly includes the reform of curriculum teaching mode, curriculum practice reform, and teaching process reform. In order to verify the effect of the proposed new model on the teaching quality of machine learning courses, this article also proposes an evaluation method based on intelligent technology. Firstly, the feasibility of evaluation based on intelligent technology is described. Secondly, it lists the application details of the existing teaching evaluation based on intelligent technology. Finally, a novel teaching quality evaluation system based on intelligent technology is proposed. The system collects student facial expression data and uses classification algorithms to make classification decisions on the data. The result of the decision can give feedback on the quality of classroom teaching. The comparison of experiments based on different intelligent technologies shows that the teaching quality evaluation system proposed in this article is feasible and effective.

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Todd, P. M. "Machine intelligence-the animat path to intelligent adaptive behaviour." Computer 25, no. 11 (1992): 78. http://dx.doi.org/10.1109/2.166420.

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Wu, Liping, and Xiaobing Liao. "Intelligent Machine Evolutionary Algorithm Learning Based on Artificial Intelligence." Procedia Computer Science 228 (2023): 1016–22. http://dx.doi.org/10.1016/j.procs.2023.11.133.

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Zhang, Jing, and Zhaochun Li. "Intelligent Tea-Picking System Based on Active Computer Vision and Internet of Things." Security and Communication Networks 2021 (November 8, 2021): 1–8. http://dx.doi.org/10.1155/2021/5302783.

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Intelligent farming machines are becoming a new trend in modern agriculture. The intelligence and automation allow planting to become data-driven, leading to more timely and cost-effective production and management of farms and improving the quality and output of farm products. This paper presents a proposal for developing a type of intelligent tea picking machine based on active computer vision and Internet of Things (IoT) techniques. The intelligent tea picking machine possesses an active vision system for new tip positioning and can automatically implement tea picking operation in the natural environment. The active vision system provided with a cross-light path of projection and camera is designed according to the actual characteristics of picking surface, where new tips can be recognized by referring to the color factor and their height information is easily acquired by fringe projection profilometry. Furthermore, the machine attaches wireless communication equipment to transmit the real-time status of the tea picking process to an intermediary platform and eventually to the Internet for extensive data analysis. The data such as color factor and quantity of new tips collected through IoT can be used for different quality and production evaluations. The focus of this paper can promote the automation and intelligence of tea pickers and agricultural machinery.

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Ast., Professor Sayema Sadiq Shaikh, Professor Sonali Shirish Ingle Ast, and Shreyash Chandrakant Dighe Mr. "To study impact of Artificial Intelligence in Voice Recognization." International Journal of Advance and Applied Research 10, no. 4 (2023): 129–31. https://doi.org/10.5281/zenodo.7791055.

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Artificial intelligence is a term used for demonstrating the intelligence exhibited by machines while operating effectively. Speech is been made understandable to the computer or machine by the means of voice recognition. It is frequently employed for commercial, military, and business purposes. Voice or speaker recognition refers to a machine's or program's capability to accept and read pronunciation or grasp and execute verbal directives. Voice recognition has helped with the advancement of AI and intelligent assistants such as Amazon's Alexa, Apple's Siri, and Microsoft's Cortana.

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Prokopowicz, Dariusz, and Mirosław Matosek. "THE CONCEPT OF MANAGING THE CONCEPT OF MANAGING THE DEVELOPMENT OF ARTIFICIAL INTELLIGENCE TECHNOLOGY BASED ON THE PREMISE OF REDUCING THE THREAT OF POTENTIAL REBELLION OF INTELLIGENT MACHINES." International Journal of Legal Studies ( IJOLS ) 18, no. 2 (2024): 191–222. https://doi.org/10.5604/01.3001.0054.9847.

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This article presents the key aspects of the concept of managing the development of artifi-cial intelligence technologies, based on the assumption of reducing the threat of a potential intelligent machine rebellion. The content of this article is based on the idea that AI devel-opment brings great benefits, but also raises concerns, including the possibility of a poten-tial rebellion by intelligent machines. Autonomous AI systems, capable of making deci-sions without human involvement, raise questions about their potential to act against human interests. Visions of such threats, present in science fiction literature, have gained relevance in light of advancements in machine learning and robotics. These concerns relate to the possibility that AI could independently develop and modify its algorithms, exceeding human control. Therefore, the management of AI technology development should be carried out in such a way as to effectively reduce the threats of a potential rebellion by intelligent machines and limit the risks of negative consequences resulting from an overly liberal, uncontrolled development of AI technology applications.

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Njeri, Ndung’u Rachael. "Data Preparation For Machine Learning Modelling." International Journal of Computer Applications Technology and Research 11, no. 06 (2022): 231–35. http://dx.doi.org/10.7753/ijcatr1106.1008.

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The world today is on revolution 4.0 which is data-driven. The majority of organizations and systems are using data to solve problems through use of digitized systems. Data lets intelligent systems and their applications learn and adapt to mined insights without been programmed. Data mining and analysis requires smart tools, techniques and methods with capability of extracting useful patterns, trends and knowledge, which can be used as business intelligence by organizations as they map their strategic plans. Predictive intelligent systems can be very useful in various fields as solutions to many existential issues. Accurate output from such predictive intelligent systems can only be ascertained by having well prepared data that suits the predictive machine learning function. Machine learning models learns from data input using the ‘garbage-in-garbage-out’ concept. Cleaned, pre-processed and consistent data would produce accurate output as compared to inconsistent, noisy and erroneous data.

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Moed, M. C., and G. N. Saridis. "A Boltzmann machine for the organization of intelligent machines." IEEE Transactions on Systems, Man, and Cybernetics 20, no. 5 (1990): 1094–102. http://dx.doi.org/10.1109/21.59972.

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Olalere, Isaac O., and Oludolapo A. Olanrewaju. "Optimising Production through Intelligent Manufacturing." E3S Web of Conferences 152 (2020): 03012. http://dx.doi.org/10.1051/e3sconf/202015203012.

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Intelligent manufacturing system (IMS) has been the focus of most industries since Industry 4.0 revolution. IMS is being implemented through the integration of Internet of Things, (IoT), Cyber-Physical Systems (CPS), digital twin and big data analytics to optimize production through smart manufacturing. This research presents a conceptual approach of an adaptive clustering algorithm (ACA) for advanced manufacturing decision-making for smart machining manufacturing. The work considers product monitoring and assessment, machine health and operating parameters monitoring, as an important factor for intelligent decision making on a machining production line through the developed cyber twin of the machine tool for production optimisation. Cyber twin of the machine tool is developed which runs on a realtime sequence with the physical asset fussed with smart sensors and controllers enabled with cloud computing, IoT and data analytics. The ACA enables resources monitoring, production monitoring, machine condition monitoring, cloud feedback notification, product monitoring, and assessment, for intelligent decision-making from a cluster of similar machines using ANN clustering tool for self-aware, self-predict and self-reconfiguration in a smart machining production line to detect a cutting tool chipping of less than 0.25mm size. The method is proposed to optimise production by increasing productivity through intelligent decision and prediction for tool change, tool failure, maintenance, adjustment of operating parameters.

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Zhou, Lingyu. "Chatgpt Empowers Higher Education Middle School Students' Intelligent Adaptation Learning Problems and Path Research." Journal of Education, Humanities and Social Sciences 40 (November 7, 2024): 20–26. http://dx.doi.org/10.54097/0wv8en95.

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In today's digital age, intelligent learning is the main direction of higher education. Generative artificial intelligence represented by Chat GPT can provide more efficient intelligent services for college students' adaptive learning, that is, intelligent adaptive learning mode. This article uses the interview method to investigate the current situation of intelligent adaptation learning for college students with the help of Chat GPT and analyzes that intelligent adaptation learning has incomparable advantages in the acquisition of learning resources for college students, scene simulation, personalized and accurate scheme provision and result evaluation in the learning process. However, in the application of reality, there are also problems such as insufficient information literacy of college students, imperfect machine intelligence systems, and lack of bad environmental support. Therefore, this article pays attention to the issue of education in the era of intelligence, based on the needs of future education development, through the development of bad environment support, machine intelligence, and the development of student information literacy, to promote the intelligence transformation of higher education, and provide college students with an efficient learning path in the era of information explosion.

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Singh, Aahan, Nithin Nagaraj, Srinidhi Hiriyannaiah, and Lalit Mohan Patnaik. "ISCG." International Journal of Intelligent Information Technologies 16, no. 4 (2020): 51–67. http://dx.doi.org/10.4018/ijiit.2020100104.

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Artificial intelligence has paved the way for different areas of computing such as speech recognition and translation, object detection, machine translation, and others. One of the goals of artificial general intelligence is to simulate human thinking and rationality within machines such that they are able to perceive their environment and then perform reasonable actions based on their perception. Creating a single model that performs every single task from visual perception to actuation is currently impossible. The system must be divided into several models each of which functions independently as well also contribute to the operation of the whole intelligent machine. In this paper, an intelligent sensing and caption generation (ISCG) system is proposed which is capable of detecting living/non-living objects and states of motion in images. The system consists of two separate modules of caption generator and intelligence engine with a Convolutional Neural Network (CNN) for determining the different objects in the images. Our model yields state-of-the-art performance on benchmarked dataset.

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Bu, Xiang-li, Chen Liu, Bo Tong, and Xiao-ping Li. "Laser cutting machine assistance system based on cloud edge collaboration." Journal of Computational Methods in Sciences and Engineering 25, no. 2 (2024): 1826–34. https://doi.org/10.1177/14727978241305757.

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The safe, stable, efficient, and environmentally friendly operation of laser cutting machines is crucial for laser cutting companies to enhance productivity and ensure safe production. Real-time acquisition, analysis, and diagnosis of machine tool system operation status information provide technical support for machine tool fault diagnosis and maintenance, thereby achieving optimal operational efficiency. The advancements in edge computing and the growing application of artificial intelligence have rendered traditional laser cutting machine tool monitoring and assistance systems obsolete in the context of modern intelligent manufacturing. This paper presents a remote monitoring and assistance system for laser cutting machine tools based on cloud edge collaboration. Intelligent devices are utilised for on-site data collection, employing various communication protocols, including HTTP and WebSocket. It realises comprehensive control of the IoT platform, equipment diagnosis and data analysis on the remote expert maintenance platform, and autonomous decision-making at the edge. It also forms the corresponding web-based interface and PC and mobile monitoring and interaction software. Laboratory tests have demonstrated the system’s viability in enhancing the productivity and maintenance of laser cutting machines. It provides a cost-effective remote diagnostic and maintenance solution for laser processing companies.

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Molchanova, Regina V. "INTELLECTUAL TRANSFORMATION OF PROCESSES AS PART OF THE STRATEGIC DEVELOPMENT OF COMPANIES." EKONOMIKA I UPRAVLENIE: PROBLEMY, RESHENIYA 5/1, no. 158 (2025): 47–54. https://doi.org/10.36871/ek.up.p.r.2025.05.01.006.

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The article considers intelligent transformation as a stage of digital evolution based on the integration of artificial intelligence, machine learning and data analytics into production processes to improve the adaptability and strategic sustainability of business. The transition to management based on cognitive and algorithmic models is revealed, ensuring the autonomous functioning of organizations due to intelligent data processing. The difference between digitalization and intelligent transformation, which creates new management models based on artificial intelligence, is revealed. Intelligent transformation ensures the transition from digital automation to self-governing and adaptive systems capable of increasing sustainability and competitiveness in the face of global challenges. The key components of intelligent transformation, big data analytics, cognitive algorithms, digital twins and adaptive systems, are presented as the basis for building an intelligently active organization focused on automation and predictive management in the face of multiparameter uncertainty. Intelligent optimization of business processes is summarized as a tool for improving operational efficiency and a factor in strategic development that contributes to the formation of innovative-active organizational models.

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Magdy, Mona, Salama Abu-Zaid, and Mahmoud A. Elwany. "Artificial intelligent techniques based on direct torque control of induction machines." International Journal of Power Electronics and Drive Systems (IJPEDS) 12, no. 4 (2021): 2070. http://dx.doi.org/10.11591/ijpeds.v12.i4.pp2070-2082.

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The direct torque control (DTC) system, which is based on induction machine drive is a developed and simple control method. It allows high dynamic performance with very simple hysteresis control scheme; However, its disadvantages are high current, torque, and flux ripple. In this paper, DTC of induction machine drive has been improved by using the applications of artificial intelligence (AI) approaches to reduce the current, torque, and flux ripples and also get better performance of the machines. At the conclusion of this study, the outcomes of traditional DTC and artificial intelligent methods are compared. By the program MATLAB/SIMULINK, the modeling and simulation results of the DTC system for induction machine (IM) have been proposed.

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Journal articles on the topic 'Intelligent machine'

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