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Journal articles on the topic 'Machine theory of collective intelligence'

Author: Grafiati

Published: 10 December 2022

Last updated: 31 July 2025

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1

Canonico, Lorenzo Barberis, Christopher Flathmann, and Nathan McNeese. "The Wisdom of the Market: Using Human Factors to Design Prediction Markets for Collective Intelligence." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 63, no. 1 (2019): 1471–75. http://dx.doi.org/10.1177/1071181319631282.

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There is an ever-growing literature on the power of prediction markets to harness “the wisdom of the crowd” from large groups of people. However, traditional prediction markets are not designed in a human-centered way, often restricting their own potential. This creates the opportunity to implement a cognitive science perspective on how to enhance the collective intelligence of the participants. Thus, we propose a new model for prediction markets that integrates human factors, cognitive science, game theory and machine learning to maximize collective intelligence. We do this by first identifyi

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Dzyaloshinsky, I. M. "Artificial Intelligence: A Humanitarian Perspective." Vestnik NSU. Series: History and Philology 21, no. 6 (2022): 20–29. http://dx.doi.org/10.25205/1818-7919-2022-21-6-20-29.

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The article is devoted to the study of the features of human intelligence and the intelligence of complex computer systems, usually referred to as artificial intelligence (AI). As a hypothesis, a statement was formulated about a significant difference between human and artificial intelligence. Human intelligence is a product of a multi-thousand-year history of the development and interaction of three interrelated processes: 1) the formation and development of the human personality; 2) the formation of complex network relationships between members of the social community; 3) collective activity

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Barberis Canonico, Lorenzo, Nathan J. McNeese, and Chris Duncan. "Machine Learning as Grounded Theory: Human-Centered Interfaces for Social Network Research through Artificial Intelligence." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 62, no. 1 (2018): 1252–56. http://dx.doi.org/10.1177/1541931218621287.

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Internet technologies have created unprecedented opportunities for people to come together and through their collective effort generate large amounts of data about human behavior. With the increased popularity of grounded theory, many researchers have sought to use ever-increasingly large datasets to analyze and draw patterns about social dynamics. However, the data is simply too big to enable a single human to derive effective models for many complex social phenomena. Computational methods offer a unique opportunity to analyze a wide spectrum of sociological events by leveraging the power of

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Kasthurirengan, Arulmozhi. "Analyzing the Role of AI/ML in Optimizing Retail." International Scientific Journal of Engineering and Management 02, no. 05 (2023): 1–8. https://doi.org/10.55041/isjem00692.

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The aim of the study was to analyze the role of artificial intelligence and machine learning in optimizing supply chain processes Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources, preferably because of its low-cost advantage as compared to field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: Artificial intelligence (AI) and machine learning (ML) pl

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Mwangi, Jackson. "Analyzing the Role of Artificial Intelligence and Machine Learning in Optimizing Supply Chain Processes in Kenya." International Journal of Supply Chain Management 9, no. 1 (2024): 39–50. http://dx.doi.org/10.47604/ijscm.2322.

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Purpose: The aim of the study was to analyze the role of artificial intelligence and machine learning in optimizing supply chain processes Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: Artificial intelligence (AI) and ma

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Orallo, José Hernández. "Heasuring (machine) intelligence universally: An interdisciplinary challenge." Acta Europeana Systemica 4 (July 13, 2020): 37–40. http://dx.doi.org/10.14428/aes.v4i1.57073.

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Artificial intelligence (Al) is having a deep impact on the way humans work, communicate and enjoy their leisure time. Al systems have been traditionally devised to solve specific tasks, such as playing chess, diagnosing a disease or driving a car. However, more and more Al systems are now being devised to be generally adaptable, and learn to solve a variety of tasks or to assist humans and organisations in their everyday tasks. As a result, an increasing number of robots, bots, avatars and 'smart' devices are enhancing our capabilities as individuals, collectives and humanity as a whole. What

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Petrina, Denis. "THE PROBLEMATIC OF ARTIFICIAL INTELLIGENCE (AI) IN COGNITIVE CAPITALISM: TOWARD POSTHUMANIST CONTOURS OF THE NEW COGNITARIAT." Topos 1, no. 1-2025 (2025): 175–203. https://doi.org/10.61095/815-0047-2025-1-175-203.

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This paper examines the problematic of artificial intelligence (AI) through the lens of contemporary critical theory, offering a dual analytical perspective. On one hand, AI is explored as a symptom of cognitive capitalism, which operates through its key mechanisms, such as modulation, control, and the generation of informational surplus value. On the other hand, the paper raises the issue of exploiting hybrid human-machine labor, emphasizing the need to transcend anthropocentric models and reconceptualize solidarity in a posthumanist framework. In the first section, AI is analyzed as a form o

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Liang, Thow Yick. "The inherent structure and dynamic of intelligent human organizations." Human Systems Management 21, no. 1 (2002): 9–19. http://dx.doi.org/10.3233/hsm-2002-21102.

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As humankind ventures deeper into the intelligence era, a totally re-defined mindset is essential to ensure its continuity. With the emerging new environment, human organizations must behave as intelligent beings, in the same manner as biological entities are competing for survival in an ecological system. They must learn, self-organize, adapt, compete and evolve. Thus, human systems can no longer be like machine. Consequently, the structures and characteristics of the industrial era will have to be dismantled. This shift in paradigm requires all human organizations to re-design their structur

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Kamensky, E. G., A. V. Mayakova, A. Y. Ogurtsova, and M. A. Huseynov. "University 4.0: Contours of Post-Industrial Manifestations In The Optics Of The Triple Helix Model." Proceedings of the Southwest State University. Series: Economics. Sociology. Management 14, no. 1 (2024): 271–82. http://dx.doi.org/10.21869/2223-1552-2024-14-1-271-282.

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Relevance. Universities, as institutional organizations, are subject to the greatest reform in the transforming matrix of goals, values and norms of building the Future. In this regard, the problem of conceptualizing the ultra-new model of the University of the fourth generation (4.0) is the most relevant for science and social sciences.The purpose of this study is to consider and analyze the conceptual foundations reflected in the scientific manifestations of the formation of the fourth generation University model (4.0) as a subject of the “triple helix".Objectives. To analyze the concepts, i

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Liang, Thow Yick. "The new intelligence leadership strategy for iCAS." Human Systems Management 26, no. 2 (2007): 111–22. http://dx.doi.org/10.3233/hsm-2007-26204.

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As humanity becomes more dependent on information and knowledge, the current concepts, theories and practices associated with leadership strategy have to be transformed. Fundamentally, the influence of the knowledge-intensive, fast-changing and more complex environment has initiated a shift in the mindset, strategic thinking, ability and style in the new generation of leaders. In addition, for all categories of human organizations (economics, business, social, education and political) their members are becoming better educated and informed, and consequently they are more sophisticated interact

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Tuwio, Namuri Migo. "LOGO DESIGN BASED ON ARTIFICIAL INTELLIGENCE (AI)." DeKaVe 17, no. 2 (2024): 151–70. https://doi.org/10.24821/dkv.v17i2.13890.

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The advancement of artificial intelligence (AI) has disrupted various aspects of human life, including the fields of art and design. This technology has proven to be a valuable tool in helping individuals create corporate identity designs (logos) quickly, cheaply, easily, and with a wide variety of options. Its open-source nature allows anyone, skilled or unskilled, to generate a logo without being bound by traditional, complex, and step-by-step methods. The continuous improvement of AI-based logo maker applications has the potential to shift the position of designers who tend to work with a “

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Chen, Zhengxin. "Learning about Learners: System Learning in Virtual Learning Environment." International Journal of Computers Communications & Control 3, no. 1 (2008): 33. http://dx.doi.org/10.15837/ijccc.2008.1.2372.

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Virtual learning is not just about a set of useful IT tools for learning. From an examination on where virtual learning stands in the overall learning spectrum, we point out the important impact of natural computing on virtual learning. We survey and analyze selected literature on important role of natural computing aspects, such as emergence (using swarm intelligence to achieve collective intelligence) and emotion, to virtual learning. In addition, in order to effectively incorporate these aspects into virtual learning, we propose using infrastructural support for virtual learning through sys

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Kale, Ashwini. "The Significance of Statistics in Artificial Intelligence." International Journal for Research in Applied Science and Engineering Technology 12, no. 3 (2024): 1020–24. http://dx.doi.org/10.22214/ijraset.2024.58985.

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Abstract: Artificial intelligence is a fast-expanding subject. The aim of artificial intelligence is to use machine learning and algorithms to build intelligent computers that have human-like thought and behavior. Statistics plays a pivotal role in the development and advancement of Artificial Intelligence. Statistics is a branch of science which deals with study of Collection, Presentation, Analysis and Interpretation of data. Statistical techniques enhance the reliability of Artificial intelligence models and ensure informed decision-making. Combining statistical approaches with Artificial i

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Pandey, Rohit. "Application of Artificial Intelligence in Predicting Machining Surface Quality." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 9, no. 2 (2018): 518–28. http://dx.doi.org/10.17762/turcomat.v9i2.13856.

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Achieving high-quality machining surface finishes is crucial in numerous manufacturing industries, as it directly impacts the performance and reliability of machined components. Traditionally, predicting machining surface quality involves extensive trial-and-error experiments, which are time-consuming, costly, and often impractical for complex machining processes. In recent years, the application of artificial intelligence (AI) techniques, particularly machine learning algorithms, has emerged as a promising approach for predicting machining surface quality accurately and efficiently. This abst

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Łukaszyk, Szymon, and Wawrzyniec Bieniawski. "Assembly Theory of Binary Messages." Mathematics 12, no. 10 (2024): 1600. http://dx.doi.org/10.3390/math12101600.

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Using assembly theory, we investigate the assembly pathways of binary strings (bitstrings) of length N formed by joining bits present in the assembly pool and the bitstrings that entered the pool as a result of previous joining operations. We show that the bitstring assembly index is bounded from below by the shortest addition chain for N, and we conjecture about the form of the upper bound. We define the degree of causation for the minimum assembly index and show that, for certain N values, it has regularities that can be used to determine the length of the shortest addition chain for N. We s

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Firza, Syafiq Azzumar. "Literatur review: Analisis Dampak AI bagi Dunia Pendidikan." Pelita Teknologi 18, no. 1 (2023): 45–54. http://dx.doi.org/10.37366/pelitatekno.v18i1.3381.

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Artificial intelligence is a system developed in research and capable of innovation, mimicking a machine or computer, that has intelligence equal to or greater than humans, that adapts, makes decisions cognitively, and learns. Specifically, we will explore various aspects of education, including management, teaching, and learning, and determine how artificial intelligence will impact education. This research utilizes a retrospective approach technique that consists of collecting data and secondary materials or conducting surveys. We help explain research and development by using, theory, and e

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Yasir, Muhammad, Abdoul Jelil Niang, Md Sakaouth Hossain, Qamar Ul Islam, Qian Yang, and Yuhang Yin. "Ranking Ship Detection Methods Using SAR Images Based on Machine Learning and Artificial Intelligence." Journal of Marine Science and Engineering 11, no. 10 (2023): 1916. http://dx.doi.org/10.3390/jmse11101916.

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We aimed to improve the performance of ship detection methods in synthetic aperture radar (SAR) images by utilizing machine learning (ML) and artificial intelligence (AI) techniques. The maritime industry faces challenges in collecting precise data due to constantly changing sea conditions and weather, which can affect various maritime operations, such as maritime security, rescue missions, and real-time monitoring of water boundaries. To overcome these challenges, we present a survey of AI- and ML-based techniques for ship detection in SAR images that provide a more effective and reliable way

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Moore, Phoebe V., Kendra Briken, and Frank Engster. "Machines and measure." Capital & Class 44, no. 2 (2020): 139–44. http://dx.doi.org/10.1177/0309816820902016.

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This Special Issue, entitled ‘Machines & Measure’, is largely the dissemination from a workshop held at University of Leicester School of Business, organised by editor Phoebe V Moore, for the Conference for Socialist Economists South Group in February 2018, which was hosted by the University of Leicester School of Business, Philosophy and Political Economy Centre. Not all the authors in the Special Issue were speakers at the event, but this collection provides a carefully selected, representative collection of articles and essays which address the questions and disturbances that drove the

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Xiao, Guannan, and Pikshy Fan. "Leveraging metaphors in qualitative machine translators in the interpretation of emotion." Journal of Infrastructure, Policy and Development 8, no. 12 (2024): 7039. http://dx.doi.org/10.24294/jipd.v8i12.7039.

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The idea of emotions that is concealed in human language gives rise to metaphor. It is challenging to compute and develop a framework for emotions in people because of its detachment and diversity. Nonetheless, machine translation heavily relies on the modeling and computation of emotions. When emotion metaphors are calculated into machine translation, the language is significantly more colorful and satisfies translating criteria such as truthfulness, creativity and beauty. Emotional metaphor computation often uses artificial intelligence (AI) and the detection of patterns and it needs massive

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Zeng, Xiaoxin. "Research on the paradoxes in the artificial intelligence images." Applied and Computational Engineering 5, no. 1 (2023): 75–80. http://dx.doi.org/10.54254/2755-2721/5/20230534.

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There is a wide argument about the development of artificial intelligence and whether it has emotions right now, conveying concern about Artificial Intelligence in the future. While people have not formed a consensus about Artificial Intelligence, even in the technical development field, this article explores a paradox in the common recognition of Artificial Intelligence image, which is the mixture of fiction and reality, collection and individual, by focusing on media served as extensions of the body and perspective, and the difference between a world in artwork and reality. The article is go

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KAMYSHOVA, G. N. "MODELING OF NEURAL PREDICTIVE CONTROL OF IRRIGATION MACHINES." Prirodoobustrojstvo, no. 1 (2021): 14–22. http://dx.doi.org/10.26897/1997-6011-2021-1-14-22.

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The purpose of the study is to develop new scientific approaches to improve the efficiency of irrigation machines. Modern digital technologies allow the collection of data, their analysis and operational management of equipment and technological processes, often in real time. All this allows, on the one hand, applying new approaches to modeling technical systems and processes (the so-called “data-driven models”), on the other hand, it requires the development of fundamentally new models, which will be based on the methods of artificial intelligence (artificial neural networks, fuzzy logic, mac

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Sen, Wang, Zhu Xiaomei, and Deng Lin. "Impact of Job Demands on Employee Learning: The Moderating Role of Human–Machine Cooperation Relationship." Computational Intelligence and Neuroscience 2022 (December 6, 2022): 1–11. http://dx.doi.org/10.1155/2022/7406716.

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New artificial intelligence (AI) technologies are applied to work scenarios, which may change job demands and affect employees’ learning. Based on the resource conservation theory, the impact of job demands on employee learning was evaluated in the context of AI. The study further explores the moderating effect of the human–machine cooperation relationship between them. By collecting 500 valid questionnaires, a hierarchical regression for the test was performed. Results indicate that, in the AI application scenario, a U-shaped relationship exists between job demands and employee learning. Seco

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Brown, Michael. "Influence of Artificial Intelligence on Credit Risk Assessment in Banking Sector." International Journal of Modern Risk Management 2, no. 1 (2024): 24–33. http://dx.doi.org/10.47604/ijmrm.2641.

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Purpose: The aim of the study was to examine the influence of artificial intelligence on credit risk assessment in banking sector. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: The study found that AI-driven models demonstrate super

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Kabanda, Gabriel. "An Evaluation of Big Data Analytics Projects and the Project Predictive Analytics Approach." Oriental journal of computer science and technology 12, no. 4 (2020): 132–46. http://dx.doi.org/10.13005/ojcst12.04.01.

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Big Data is the process of managing large volumes of data obtained from several heterogeneous data types e.g. internal, external, structured and unstructured that can be used for collecting and analyzing enterprise data. The purpose of the paper is to conduct an evaluation of Big Data Analytics Projects which discusses why the projects fail and explain why and how the Project Predictive Analytics (PPA) approach may make a difference with respect to the future methods based on data mining, machine learning, and artificial intelligence. A qualitative research methodology was used. The research d

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Chen, Mercy. "Role of Artificial Intelligence in Marketing Automation in China." International Journal of Strategic Marketing Practice 6, no. 2 (2024): 25–35. http://dx.doi.org/10.47604/ijsmp.2745.

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Purpose: The aim of the study was to examine the Role of Artificial Intelligence in Marketing Automation in China Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: The study found that the role of artificial intelligence (AI) in marketi

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Naser, Marwah Abdulrazzaq, Aso Ahmed Majeed, Muntadher Alsabah, Taha Raad Al-Shaikhli, and Kawa M. Kaky. "A Review of Machine Learning’s Role in Cardiovascular Disease Prediction: Recent Advances and Future Challenges." Algorithms 17, no. 2 (2024): 78. http://dx.doi.org/10.3390/a17020078.

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Cardiovascular disease is the leading cause of global mortality and responsible for millions of deaths annually. The mortality rate and overall consequences of cardiac disease can be reduced with early disease detection. However, conventional diagnostic methods encounter various challenges, including delayed treatment and misdiagnoses, which can impede the course of treatment and raise healthcare costs. The application of artificial intelligence (AI) techniques, especially machine learning (ML) algorithms, offers a promising pathway to address these challenges. This paper emphasizes the centra

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Srivastava, Neeraj. "Development of a Machine Learning Model for Predicting Fracture Behaviour of Materials Using AI." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 9, no. 2 (2018): 621–31. http://dx.doi.org/10.17762/turcomat.v9i2.13865.

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Fracture behaviour prediction of materials is a critical aspect in various industries, including aerospace, automotive, and manufacturing. Accurate prediction of fracture behaviour can aid in designing robust materials and structures, enhancing safety, and optimizing performance. In this study, we propose the development of a machine learning model for predicting fracture behaviour of materials using artificial intelligence (AI) techniques. The methodology involves the collection and pre-processing of a comprehensive dataset comprising material properties, structural characteristics, and fract

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Neogy, Taposh Kumar. "Multimodal Learning Analysis via Machine Learning and Deep Learning Methodologies." Asian Journal of Applied Science and Engineering 7, no. 1 (2018): 65–74. http://dx.doi.org/10.18034/ajase.v7i1.47.

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The world we live in is purely multimodal in nature. We can see objects, hear sounds, smell different sorts of scents, feel things, and taste various flavors. The word ‘Modality’ refers to something that occurs or something that can be experienced. An experience is presented as multimodal only when it includes some of the modalities found in the world. In order to gain recognition in understanding our general surroundings, artificial intelligence should be able to understand such multimodal perspectives. On the other hand, multimodal machine learning refers to the development of models that ca

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Silva, Matheus Alencar da, Bonfim Amaro Junior, Ramon Rudá Brito Medeiros, and Plácido Rogério Pinheiro. "A Neuroevolutionary Model to Estimate the Tensile Strength of Manufactured Parts Made by 3D Printing." Algorithms 15, no. 8 (2022): 263. http://dx.doi.org/10.3390/a15080263.

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Three-dimensional printing has advantages, such as an excellent flexibility in producing parts from the digital model, enabling the fabrication of different geometries that are both simple or complex, using low-cost materials and generating little residue. Many technologies have gained space, highlighting the artificial intelligence (AI), which has several applications in different areas of knowledge and can be defined as any technology that allows a system to demonstrate human intelligence. In this context, machine learning uses artificial intelligence to develop computational techniques, aim

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Manjula, Nishchai Jayanna, Kiran Randhi, and Srinivas Reddy Bandarapu. "Federated Learning for Healthcare: Balancing Data Privacy and Model Accuracy." American Journal of Computing and Engineering 8, no. 1 (2025): 69–80. https://doi.org/10.47672/ajce.2634.

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Purpose: Federated Learning (FL) is transforming the way machine learning models are trained by allowing institutions to collaborate without sharing sensitive data. This is especially valuable in healthcare, where patient records are often stored separately across hospitals and research centers. This decentralized approach allows healthcare providers, researchers, and organizations to leverage collective intelligence from distributed datasets, leading to advancements in diagnostics, treatment personalization, and patient outcomes. Materials and Methods: However, the adoption of FL in healthcar

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Keyhan, Javad. "Designing a Model for an AI-Based Intelligent Assistant for Personalized Learning in Higher Education." International Journal of Technology in Education and Science 9, no. 2 (2025): 255–69. https://doi.org/10.46328/ijtes.616.

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In recent years, remarkable advancements in artificial intelligence technology have created new opportunities for transforming educational systems and enhancing student learning. This study focuses on designing a model for an AI-based intelligent assistant to provide a personalized learning experience in higher education. A qualitative approach and grounded theory strategy were used to conduct the research. The study population included all experts, professors, and senior managers in the fields of educational sciences and software engineering in higher education, with 21 individuals selected t

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Hedar, Abdel-Rahman, Majid Almaraashi, Alaa E. Abdel-Hakim, and Mahmoud Abdulrahim. "Hybrid Machine Learning for Solar Radiation Prediction in Reduced Feature Spaces." Energies 14, no. 23 (2021): 7970. http://dx.doi.org/10.3390/en14237970.

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Solar radiation prediction is an important process in ensuring optimal exploitation of solar energy power. Numerous models have been applied to this problem, such as numerical weather prediction models and artificial intelligence models. However, well-designed hybridization approaches that combine numerical models with artificial intelligence models to yield a more powerful model can provide a significant improvement in prediction accuracy. In this paper, novel hybrid machine learning approaches that exploit auxiliary numerical data are proposed. The proposed hybrid methods invoke different ma

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Hamdi, Sami Abdullah, Rawdah Abu Hashem, Wael Ali Holbah, Yaseen Ali Azi, and Saifaddin Y. Mohammed. "Proverbs Translation for Intercultural Interaction: A Comparative Study between Arabic and English Using Artificial Intelligence." World Journal of English Language 13, no. 7 (2023): 282. http://dx.doi.org/10.5430/wjel.v13n7p282.

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Proverbs are a source of wisdom and morals that have been passed on from one generation to the next throughout history. Through intercultural interaction, it appears that some proverbs were either translated or have equivalents in different languages and cultures. This study used artificial intelligence, specifically machine learning techniques, to examine five equivalent proverbs in Arabic and English. Emphasis was placed on the occurrence of equivalent proverbs in different contexts through a collection of actual language use. A topic modeling algorithm was applied to a dataset for each prov

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Mwavali, Asiema. "Framework for Mitigating Phishing E-mail in the Kenyan Banking Industry Using Artificial Intelligence (AI)." International Journal of Technology and Systems 9, no. 2 (2024): 40–66. http://dx.doi.org/10.47604/ijts.2781.

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Purpose: Phishing is a significant cybercrime threat that affects individuals and organizations globally, including the banking industry in Kenya. The sophistication of phishing attacks continues to increase, and it is increasingly challenging traditional security measures to mitigate these threats. The purpose of this thesis is to build a framework for mitigating phishing e-mail attacks in the banking industry in Kenya using artificial intelligence. Phishing emails are among the most common techniques of cyber-attacks utilized by assailants to gain unauthorized access to sensitive information

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Strang, Kenneth David. "Cybercrime Risk Found in Employee Behavior Big Data Using Semi-Supervised Machine Learning with Personality Theories." Big Data and Cognitive Computing 8, no. 4 (2024): 37. http://dx.doi.org/10.3390/bdcc8040037.

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A critical worldwide problem is that ransomware cyberattacks can be costly to organizations. Moreover, accidental employee cybercrime risk can be challenging to prevent, even by leveraging advanced computer science techniques. This exploratory project used a novel cognitive computing design with detailed explanations of the action-research case-study methodology and customized machine learning (ML) techniques, supplemented by a workflow diagram. The ML techniques included language preprocessing, normalization, tokenization, keyword association analytics, learning tree analysis, credibility/rel

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Petrov, Ivan, and Toni Janevski. "5G Mobile Technologies and Early 6G Viewpoints." European Journal of Engineering Research and Science 5, no. 10 (2020): 1240–46. http://dx.doi.org/10.24018/ejers.2020.5.10.2169.

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Design of each successor mobile technology assures improved and advanced functionality features compared to its predecessor. Machine Learning and generally Artificial Intelligence (AI) is becoming necessity for further expansion of the beyond 5G mobile world. AI-assisted IoT services, data collection, analytics and storage should become native in the beyond 5G era. 5G introduces New Radio (NR) in sub-6 GHz bands and also in mmWave bands above 24 GHz, network virtualization and softwarization, which means that Next Generation Core and 5G NR access network are built by using different functions

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Petrov, Ivan, and Toni Janevski. "5G Mobile Technologies and Early 6G Viewpoints." European Journal of Engineering and Technology Research 5, no. 10 (2020): 1240–46. http://dx.doi.org/10.24018/ejeng.2020.5.10.2169.

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Design of each successor mobile technology assures improved and advanced functionality features compared to its predecessor. Machine Learning and generally Artificial Intelligence (AI) is becoming necessity for further expansion of the beyond 5G mobile world. AI-assisted IoT services, data collection, analytics and storage should become native in the beyond 5G era. 5G introduces New Radio (NR) in sub-6 GHz bands and also in mmWave bands above 24 GHz, network virtualization and softwarization, which means that Next Generation Core and 5G NR access network are built by using different functions

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Wang, Zhenhua, Yu Huang, Yuanming Liu, and Tao Wang. "Prediction Model of Strip Crown in Hot Rolling Process Based on Machine Learning and Industrial Data." Metals 13, no. 5 (2023): 900. http://dx.doi.org/10.3390/met13050900.

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The strip crown in hot rolling has the characteristics of multivariablity, strong coupling and, nonlinearity. It is difficult to describe accurately using a traditional mechanism model. In this paper, based on the industrial data of a hot continuous rolling field, the modeling dataset of a strip steel prediction model is constructed through the collection and collation of the on-site data. According to the classical strip crown control theory, the important process parameters that affect the strip crown are determined as input variables for the data-driven model. Some new intelligent strip cro

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Carvalho, Nadson Lucio De Sousa. "Digital Resilience: How Hard And Soft Skills Are Redefining Finance Professionals." IOSR Journal of Business and Management 27, no. 5 (2025): 53–66. https://doi.org/10.9790/487x-2705045366.

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The present study aims to map and analyze the hard and soft skills considered essential for the future of finance professionals, in light of digital transformations and evolving labor market demands. To achieve this objective, a mixed methodological approach was adopted, combining literature review with empirical research through the application of a structured questionnaire to 203 finance professionals, from different regions, economic sectors, and levels of experience. The collection method included closed and open-ended questions, allowing both quantification and qualification of respondent

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West, Adam, John Clifford, and David Atkinson. "“Alexa, Build Me a Brand” — An Investigation into the I mpact of Artificial Intelligence on Branding." Journal of Business and Economics 9, no. 10 (2018): 877–87. http://dx.doi.org/10.15341/jbe(2155-7950)/10.09.2018/005.

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Brands are built by “wrapping mediocre products in emotive and social associations” (Galloway, 2016). Nike and Coca-Cola differentiate through the emotional benefits associated with their brand, not their products functional benefit — with the latter long considered the worlds’ most valuable brand (Interbrand, 2016). This brand-building model has not been scrutinised in an environment where technology is a primary driver of organisational success, not merely a support function (E&Y, 2011). Artificial Intelligence (AI) has made “giant leaps” (Hosea, 2016) — algorithms — fly our planes and b

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Dos Reis Tomás, Cecília Cristina, and António Moreira Teixeira. "Ethical Challenges in the Use of Iot in Education: On the Path to Personalization." EDEN Conference Proceedings, no. 1 (October 21, 2020): 217–26. http://dx.doi.org/10.38069/edenconf-2020-rw-0024.

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In the research on the ethical challenges related to the Internet of Things (IoT) and the personalisation of the learning process, four key categories have been identified: Security, Privacy, Automation, and Interaction. Based on this framework, using Constructivist Grounded Theory (CGT), we’ve conducted a study with twenty one actors in the field which have reflected on the advantages, risks and challenges, creating and developing theoretical solutions from technological, pedagogical, and ethical-philosophical perspectives. Coupled with the challenge of interoperability on IoT highways, the e

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Zhang, Biqian, Liping Li, Min Shu, Liu Yang, and Lei Zhao. "The Age of Anxiety: Unpacking Technological Job Insecurity and Its Impact on Workplace Innovation." Journal of Management and Sustainability 15, no. 2 (2025): 13. https://doi.org/10.5539/jms.v15n2p13.

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As technology advances at an unprecedented pace, artificial intelligence tools like ChatGPT and Deep Seek are reshaping workplaces, sparking widespread fears of job displacement among employees. This phenomenon, termed Technological Job Insecurity (TJI), goes beyond concerns of machines replacing human roles&mdash;it encompasses anxieties about being outperformed by colleagues better equipped to navigate the digital age. While innovation remains critical in such challenging times, the psychological toll of TJI often dampens employees&rsquo; ability to think creatively and contribute ne

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Zodwa Dlamini. "Influence of Big Data Analytics on Decision-Making Processes in Financial Firms in South Africa." American Journal of Data, Information and Knowledge Management 5, no. 1 (2024): 14–25. http://dx.doi.org/10.47672/ajdikm.2350.

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Purpose: The aim of the study was to assess the influence of big data analytics on decision-making processes in financial firms in South Africa. Materials and Methods: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: By harnessing vast volumes of s

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Kovacheva, Diana. "The New Subjects of Law – Are Artificial Intelligence Systems Already among Us?" De Jure 13, no. 2 (2022): 227–49. http://dx.doi.org/10.54664/brem6290.

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The study explores the issue of legal personality and liability of artificial intelligence (AI) systems. A real AI should have a will and self-awareness, but, at this point, there are mainly systems with a collective “cloud” intelligence that is located outside of them, supported by people (Sofia, the chatbot Miraya, the chatbot Tai, the xenobots). It is important to be clear about the fact whether robots are still only a “means”, a “tool” that facilitates human life, or whether they already have qualities that make them independent entities. Currently, AI systems are treated as objects of law

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Micah, Ezekiel Elton Mike, Ibrahim Halidu Saidu, Taiwo Ibitomi, and Bello Sambo Sanusi. "Digital Forensics in the Era of Cybercrime: Emerging Trends and Challenges for Forensic Accountants in Nigeria." European Journal of Accounting, Auditing and Finance Research 11, no. 9 (2023): 85–100. http://dx.doi.org/10.37745/ejaafr.2013/vol11n985100.

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This study examined the impact of technology on digital forensics and the challenges faced by forensic accountants in the era of cybercrime. The study highlights the four dimensions in which technology has an impact on digital forensics: technical, legal, organizational, and educational. The paper also discusses how emerging technologies such as artificial intelligence and machine learning can be used in digital forensics, along with the challenges they present. Cloud computing is also examined, and the challenges it poses for forensic accountants who need to access and analyze financial data

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S Neves, Fabio, and Marc Timme. "Bio-inspired computing by nonlinear network dynamics—a brief introduction." Journal of Physics: Complexity 2, no. 4 (2021): 045019. http://dx.doi.org/10.1088/2632-072x/ac3ad4.

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Abstract The field of bio-inspired computing has established a new Frontier for conceptualizing information processing, aggregating knowledge from disciplines as different as neuroscience, physics, computer science and dynamical systems theory. The study of the animal brain has shown that no single neuron or neural circuit motif is responsible for intelligence or other higher-order capabilities. Instead, complex functions are created through a broad variety of circuits, each exhibiting an equally varied repertoire of emergent dynamics. How collective dynamics may contribute to computations sti

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Schwan, Constanze, and Wolfram Schenck. "A three-step model for the detection of stable grasp points with machine learning." Integrated Computer-Aided Engineering 28, no. 4 (2021): 349–67. http://dx.doi.org/10.3233/ica-210659.

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Robotic grasping in dynamic environments is still one of the main challenges in automation tasks. Advances in deep learning methods and computational power suggest that the problem of robotic grasping can be solved by using a huge amount of training data and deep networks. Despite these huge accomplishments, the acceptance and usage in real-world scenarios is still limited. This is mainly due to the fact that the collection of the training data is expensive, and that the trained network is a black box. While the collection of the training data can sometimes be facilitated by carrying it out in

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Peng, Zikang. "New Media Marketing Strategy Optimization in the Catering Industry Based on Deep Machine Learning Algorithms." Journal of Mathematics 2022 (February 4, 2022): 1–10. http://dx.doi.org/10.1155/2022/5780549.

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With the in-depth development of new-generation network technologies such as the Internet, big data, and cloud intelligence, people can obtain massive amounts of information on mobile phones or mobile platforms. The era of unreachable big data has arrived, which raises questions for the development of corporate marketing. With the development of Internet technology, people use mobile terminals for longer and longer periods of time. New media has gradually become the mainstream of the media arena. It has distinctive features such as freedom to find audiences, diverse content forms, and timeline

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Mwavali, Asiema. "Combating Phishing in Kenya: A Supervised Learning Model for Enhanced Email Security in Kenyan Financial Institutions." International Journal of Technology and Systems 9, no. 4 (2024): 23–36. http://dx.doi.org/10.47604/ijts.2820.

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Purpose: Phishing is a serious cybercrime problem that puts people and organizations at risk all around the world, especially in Republic of Kenya's financial institutions. Modern solutions are required because traditional security measures are being challenged by the growing sophistication of phishing attempts. The goal of this thesis is to use artificial intelligence (AI) to create a supervised machine learning model that will alleviate phishing email attacks in the Kenyan financial institutions. Attackers frequently use phishing emails as a means of obtaining unauthorized access to private

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Vishnoi, Susheela, Saneh Lata Yadav, Ashok Kumar Saini, and Prashant Vats. "Transforming Healthcare Delivery: Assessing the Role of E-Governance Strategies in IOMT and AIML-Based Medical System Administration during the Pandemic in the Indian Subcontinent." Biomedical and Pharmacology Journal 18, December Spl Edition (2025): 331–46. https://doi.org/10.13005/bpj/3091.

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This paper investigates the transformative impacts of e-governance strategies on the Internet of Medical Things (IOMT) and IOMT-based medical system administration in the context of the COVID-19 pandemic within the Indian Subcontinent, leveraging applications of Artificial Intelligence and Machine Learning (AIML). As the pandemic continues to strain healthcare systems worldwide, effective utilization of digital technologies becomes paramount in ensuring efficient healthcare delivery. E-governance initiatives play a crucial role in facilitating the integration of IOMT devices and AIML algorithm

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