Theory and Realization of Secondary Task Assignment for Multi-UAV Pickup Based on Green Scheduling by Shunqi Liu, Xi Fang, Yi Guo, Chenwei Liu, Jian Yang

“…The development of artificial intelligence technology has brought changes to various industries. …”
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Fake news and the political economy of the media: A perspective of Ghanaian journalists by Paul Achonga Kabah Kwode, Nkosinathi Selekane

“…This paper also identified the use of artificial intelligence and robotics in the creation of fake news content. …”
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Understanding designers’ switching intention to AI painting tools using the PPM framework by Yilin Liu, Ping Ji

“…Abstract In recent years, the emergence of artificial intelligence painting tools has significantly changed the creative activities and future development of designers, but studies specifically addressing designers’ inclinations to transition to AI painting tools are scarce. …”
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E-Commerce across Boarder Logistics Risk Evaluation Model Based on Improved Neural Network by Wei Qiao

“…BP neural network is a typical algorithm in artificial intelligence network. It has strong nonlinear mapping ability and is the most prominent part to solve some nonlinear problems. …”
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Survei Penelitian Metode Kecerdasan Buatan untuk Mendeteksi Ancaman Teknologi Serangan Siber by Eza Yolanda Fitria, Kusprasapta Mutijarsa

“…This research aims to map the techniques and methods of artificial intelligence to detect cyber-attack technology threats in the form of a Systematic Literature Review (SLR). …”
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MathVision: An Accessible Intelligent Agent for Visually Impaired People to Understand Mathematical Equations by Muhammad Awais Ahmad, Tauqir Ahmed, Muhammad Aslam, Amjad Rehman, Faten S. Alamri, Saeed Ali Bahaj, Tanzila Saba

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Perbandingan Metode Supervised Machine Learning untuk Prediksi Prevalensi Stunting di Provinsi Jawa Timur by M Syauqi Haris, Ahsanun Naseh Khudori, Wahyu Teja Kusuma

“…Supervised machine learning is an approach in making artificial intelligence that uses labeled data as training data. …”
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LoCS-Net: Localizing convolutional spiking neural network for fast visual place recognition by Ugur Akcal, Ugur Akcal, Ugur Akcal, Ivan Georgiev Raikov, Ekaterina Dmitrievna Gribkova, Ekaterina Dmitrievna Gribkova, Anwesa Choudhuri, Anwesa Choudhuri, Seung Hyun Kim, Mattia Gazzola, Rhanor Gillette, Rhanor Gillette, Ivan Soltesz, Girish Chowdhary, Girish Chowdhary, Girish Chowdhary

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Crime mapping features by O. V. Manzhai, А. О. Потильчак

“…Some software solutions for the implementation of the tasks of mapping criminal manifestations and the use of artificial intelligence systems for this purpose are described. …”
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Application of Image Processing Variation Model Based on Network Control Robot Image Transmission and Processing System in Multimedia Enhancement Technology by Yanmin Wu, Jinli Qi

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Structured Dynamics in the Algorithmic Agent by Giulio Ruffini, Francesca Castaldo, Jakub Vohryzek

“…Our findings bridge perspectives from algorithmic information theory (Kolmogorov complexity, compressive modeling), symmetry (group theory), and dynamics (conservation laws, reduced manifolds), offering insights into the neural correlates of agenthood and structured experience in natural systems, as well as the design of artificial intelligence and computational models of the brain.…”
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Stochastic Risk Assessment with a Lagrangian Solution for the Optimal Cost Allocation in High-Speed Rail Networks by Jing Zuo, Jianwu Dang, Min Lyu

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Micro-Grid Wind Energy Conversion Systems: Conventional and Modern Embedded Technologies - A Review by Mutiu AGBOOLA, K.A. HASSAN, T.O. AJEWOLE

“…Nonetheless, there are a few drawbacks and difficulties with the two widely utilized contemporary techniques for power quality extractions: artificially intelligent neural networks and their embedded control systems. …”
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Impact of AI and big data analytics on healthcare outcomes: An empirical study in Jordanian healthcare institutions by Rand Al-Dmour, Hani Al-Dmour, Eatedal Basheer Amin, Ahmed Al-Dmour

“…Artificial intelligence (AI) and big data analytics are transforming healthcare globally and in Jordan. …”
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Cyber security entity recognition method based on residual dilation convolution neural network by Bo XIE, Guowei SHEN, Chun GUO, Yan ZHOU, Miao YU

“…In recent years,cybersecurity threats have increased,and data-driven security intelligence analysis has become a hot research topic in the field of cybersecurity.In particular,the artificial intelligence technology represented by the knowledge graph can provide support for complex cyberattack detection and unknown cyberattack detection in multi-source heterogeneous threat intelligence data.Cybersecurity entity recognition is the basis for the construction of threat intelligence knowledge graphs.The composition of security entities in open network text data is very complex,which makes traditional deep learning methods difficult to identify accurately.Based on the pre-training language model of BERT (pre-training of deep bidirectional transformers),a cybersecurity entity recognition model BERT-RDCNN-CRF based on residual dilation convolutional neural network and conditional random field was proposed.The BERT model was used to train the character-level feature vector representation.Combining the residual convolution and the dilation neural network model to effectively extract the important features of the security entity,and finally obtain the BIO annotation of each character through CRF.Experiments on the large-scale cybersecurity entity annotation dataset constructed show that the proposed method achieves better results than the LSTM-CRF model,the BiLSTM-CRF model and the traditional entity recognition model.…”
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Enabling Fast AI-Driven Inverse Design of a Multifunctional Nanosurface by Parallel Evolution Strategies by Ashish Chapagain, Dima Abuoliem, In Ho Cho

“…In recent works, the authors proposed to leverage the evolution strategies (ES) to modify nanosurface characteristics with CFL to achieve specific functionalities such as frictional, optical, and bactericidal properties. For artificial intelligence (AI)-driven inverse design, earlier research integrates basic multiphysics principles such as dynamic viscosity, air diffusivity, surface tension, and electric potential with backward deep learning (DL) on the framework of ES. …”
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GaitRec-Net: A Deep Neural Network for Gait Disorder Detection Using Ground Reaction Force by Chandrasen Pandey, Diptendu Sinha Roy, Ramesh Chandra Poonia, Ayman Altameem, Soumya Ranjan Nayak, Amit Verma, Abdul Khader Jilani Saudagar

“…This article presents an artificial intelligence-based comprehensive investigation of ground reaction force (GRF) pattern to classify the healthy control and gait disorders using the large-scale ground reaction force. …”
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Discriminative training of spiking neural networks organised in columns for stream‐based biometric authentication by Enrique Argones Rúa, Tim Vanhamme, Davy Preuveneers, Wouter Joosen

“…SNNs have proven advantages regarding energy consumption and they are a perfect match with some proposed neuromorphic hardware chips, which can lead to a broader adoption of user device applications of artificial intelligence technologies. One of the challenges when using SNNs is the discriminative training of the network since it is not straightforward to apply the well‐known error backpropagation (EBP), massively used in traditional artificial neural networks (ANNs). …”
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Civil structural health monitoring and machine learning: a comprehensive review by Asraar Anjum, Meftah Hrairi, Abdul Aabid, Norfazrina Yatim, Maisarah Ali

“…This synthesis of advanced artificial intelligence (AI) serves as a guide, providing new researchers with knowledge about a developing field. …”
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Discovering causal models for structural, construction and defense-related engineering phenomena by M.Z. Naser

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