A Data-Intelligence-Driven Digital Twin Framework for Improving Sustainability in Logistics by Ibrahim Abdullahi, Hadi Larijani, Dimitrios Liarokapis, James Paterson, David Jones, Stewart Murray

“…As the company adopts the utilization of data intelligence as a way to collect, process and utilize data for insights, this presents an opportunity for applying artificial intelligence (AI) approaches such as reinforcement learning (RL), to identify trends, and offer recommendations for improving the sustainability and efficiency of its logistics. …”
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FTNet-HiLa: An adaptive multimodal histopathological image categorization network by Shuo Yin, Dong Zhang, YongKang Zhang, Xing Zhao, XuYing Zhao

“…The integration of artificial intelligence in medical imaging has witnessed a surge in neural network applications for pathological image classification, with Vision Transformers (ViTs) emerging as highly accurate models in general visual recognition tasks. …”
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Digital framework for georeferenced multiplatform surveillance of banana wilt using human in the loop AI and YOLO foundation models by Juan Jose Mora, Guy Blomme, Nancy Safari, Sivalingam Elayabalan, Ramasamy Selvarajan, Michael Gomez Selvaraj

“…Human in the Loop Artificial Intelligence was also utilized to enhance the ground level model’s predictions.…”
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Micro-Engagements through AI-Smartwatch Wearables for eHealth: User Experiential Discourses on Social Media by Ireen Mmatlou Manyuha, Elizabeth Lubinga

“… Globally, the use of Artificial Intelligence (AI) wearables including smartwatches has gained traction. …”
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INRNet: Neighborhood Re-Ranking-Based Method for Pedestrian Text-Image Retrieval by Kehao Wang, Yuhui Wang, Lian Xue, Qifeng Li

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The study on multi-defect detection for leather using object detection techniques by Hasan Onur Ataç, Ahmet Kayabaşı, M. Fatih Aslan

“…As a result, there is a growing demand for automated systems to detect the defects. Herein, artificial intelligence (AI) was developed to detect the defects on leather surfaces. …”
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SURVEY AND PROPOSED METHOD TO DETECT ADVERSARIAL EXAMPLES USING AN ADVERSARIAL RETRAINING MODEL by Thanh Son Phan, Quang Hua Ta, Duy Trung Pham, Phi Ho Truong

“…Artificial intelligence (AI) has found applications across various sectors and industries, offering numerous advantages to human beings. …”
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Common and distinct neural underpinnings of the association between childhood maltreatment and depression and aggressive behavior by Yuan Li, Ting Zhang, Xin Hou, Xiaoyi Chen, Yu Mao

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A novel Fruit Fly Optimization Algorithm with quasi-affine transformation evolutionary for numerical optimization and application by Ru-Yu Wang, Pei Hu, Chia-Cheng Hu, Jeng-Shyang Pan

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A multimodal multidomain multilingual medical foundation model for zero shot clinical diagnosis by Fenglin Liu, Zheng Li, Qingyu Yin, Jinfa Huang, Jiebo Luo, Anshul Thakur, Kim Branson, Patrick Schwab, Bing Yin, Xian Wu, Yefeng Zheng, David A. Clifton

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YOLOSeg with applications to wafer die particle defect segmentation by Yen-Ting Li, Yu-Cheng Chan, Chen-Che Huang, Yu-Chang Hsu, Ssu-Han Chen

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Analyzing Interdisciplinary Research Using Co-Authorship Networks by Mati Ullah, Abdul Shahid, Irfan ud Din, Muhammad Roman, Muhammad Assam, Muhammad Fayaz, Yazeed Ghadi, Hanan Aljuaid

“…It was found that “Artificial Intelligence” and “Information Storage and Retrieval”, “Natural Language Processing and Information Storage and Retrieval”, and “Human-Computer Interface” and “Database Applications” were found the most overlapping areas by acquiring an IDR score of 0.879, 0.711, and 0.663, respectively.…”
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Parameter analysis and optimization of polling-based medium access control protocol for multi-sensor communication by Jialin Guo, Fufang Li, Tian Wang, Shaobo Zhang, Yuqing Zhao

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Rapid Fluid Velocity Field Prediction in Microfluidic Mixers via Nine Grid Network Model by Qian Li, Yuwei Chen, Taotao Sun, Junchao Wang

“…The rapid advancement of artificial intelligence is transforming the computer-aided design of microfluidic chips. …”
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Comparative use of different AI methods for the prediction of concrete compressive strength by Mouhamadou Amar

“…However, accurately determining concrete properties without laboratory testing is challenging, especially when nontraditional materials, such as certain supplementary cementitious materials, are involved. Recently, artificial intelligence has become a powerful resource that enables machine learning-based forecasting using available data. …”
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Research on the Application of Deep Learning Technology Oriented to the Construction and Innovation of Smart City Image Cognition by Dan Shi, Lixin Song

“…At the same time, this research is used to answer the development dilemma of big data, summarize the development trend of big data, and explore the new changes that artificial intelligence brings to urban planning. The experimental results show that the model we designed efficiently evaluates the image of the city and can also effectively recognize the image of the city in the main urban area of Chongqing.…”
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Research on the Integrated Detection Host System of Urban Rail Transit Trains by CHEN Zhi, LYU Hongqiang

“…Specifically, the active obstacle detection subsystem is directly connected to the AI (artificial intelligence) board of the integrated host through a switch, and each of other subsystems is first connected to a front-end host for data preprocessing, and then connected to the AI board of the integrated host through a switch. …”
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Electroanalytical Methods as a Tool for Determining the Antioxidant Capacity in Blood Samples by Fernanda Gonçalves de Oliveira, Thiago da Silveira Alvares, Rodrigo de Siqueira Melo

“…Innovations such as portable devices and integration with artificial intelligence promise to further enhance accessibility and treatment personalization, despite the challenges involved in device cost and standardization. …”
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Wearable Electrochemical Biosensors for Advanced Healthcare Monitoring by Haowei Duan, Shuhua Peng, Shuai He, Shi‐Yang Tang, Keisuke Goda, Chun H. Wang, Ming Li

“…Furthermore, the challenges associated with critical issues are discussed, such as biocompatibility, biofouling, and sensor degradation, and the opportunities in materials science, nanotechnology, and artificial intelligence to overcome these limitations.…”
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Robust reinforcement learning algorithm based on pigeon-inspired optimization by Mingying ZHANG, Bing HUA, Yuguang ZHANG, Haidong LI, Mohong ZHENG

“…Reinforcement learning(RL) is an artificial intelligence algorithm with the advantages of clear calculation logic and easy expansion of the model.Through interacting with the environment and maximizing value functions on the premise of obtaining little or no prior information, RL can optimize the performance of strategies and effectively reduce the complexity caused by physical models .The RL algorithm based on strategy gradient has been successfully applied in many fields such as intelligent image recognition, robot control and path planning for automatic driving.However, the highly sampling-dependent characteristics of RL determine that the training process needs a large number of samples to converge, and the accuracy of decision making is easily affected by slight interference that does not match with the simulation environment.Especially when RL is applied to the control field, it is difficult to prove the stability of the algorithm because the convergence of the algorithm cannot be guaranteed.Considering that swarm intelligence algorithm can solve complex problems through group cooperation and has the characteristics of self-organization and strong stability, it is an effective way to be used for improving the stability of RL model.The pigeon-inspired optimization algorithm in swarm intelligence was combined to improve RL based on strategy gradient.A RL algorithm based on pigeon-inspired optimization was proposed to solve the strategy gradient in order to maximize long-term future rewards.Adaptive function of pigeon-inspired optimization algorithm and RL were combined to estimate the advantages and disadvantages of strategies, avoid solving into an infinite loop, and improve the stability of the algorithm.A nonlinear two-wheel inverted pendulum robot control system was selected for simulation verification.The simulation results show that the RL algorithm based on pigeon-inspired optimization can improve the robustness of the system, reduce the computational cost, and reduce the algorithm’s dependence on the sample database.…”
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