Measuring the Inferential Values of Relations in Knowledge Graphs by Xu Zhang, Xiaojun Kang, Hong Yao, Lijun Dong

“…Knowledge graphs, as an important research direction in artificial intelligence, have been widely applied in many fields and tasks. …”
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Hybrid deep learning approach for brain tumor classification using EfficientNetB0 and novel quantum genetic algorithm by Kerem Gencer, Gülcan Gencer

“…Therefore, multiple classification of brain tumors has gained significant interest in recent years in both the medical and computer science fields. The use of artificial intelligence and machine learning, especially in the automatic classification of brain tumors, is increasing significantly. …”
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Hyperspectral Band Selection with Unique Pixel Extraction and Adaptive Neighbor Clustering by Bing Han, Mingqing Liu, Zhenyu Ma, Ke Zhang, Yanke Xu, Jingyu Wang, Qi Wang

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3D printable and myoelectrically sensitive hydrogel for smart prosthetic hand control by Jinxin Lai, Longya Xiao, Beichen Zhu, Longhan Xie, Hongjie Jiang

“…Systematic in vivo studies were used to investigate its efficacy to control a prosthetic hand by decoding sEMG signals from the human hand via a multiple-channel readout circuit and a sophisticated artificial intelligence algorithm. Our findings demonstrate that the 3D printed gel myoelectric sensing system enables real-time and highly precise control of a prosthetic hand.…”
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Targeted Discrepancy Attacks: Crafting Selective Adversarial Examples in Graph Neural Networks by Hyun Kwon, Jang-Woon Baek

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An efficient and resilience linear prefix approach for mining maximal frequent itemset using clustering by M. Sinthuja, S. Pravinthraja, B K Dhanalakshmi, H L Gururaj, Vinayakumar Ravi, G Jyothish Lal

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Development of an AI-Enabled Q-Agent for Making Data Offloading Decisions in a Multi-RAT Wireless Network by Murk Marvi, Adnan Aijaz, Anam Qureshi, Muhammad Khurram

“…However, due to the stochastic nature of the wireless networks, it is important to take optimal actions under different conditions such that the user experience is enhanced and congestion on heavy-loaded radio access technologies (RATs) is reduced by offloading data through lower loaded RATs. Since artificial intelligence (AI)-based techniques can learn optimal actions and adapt to different conditions, in this work, we develop an AI-enabled Q-agent for making data offloading decisions in a multi-RAT wireless network. …”
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The Barcelona Historical Marriage Database and the Baix Llobregat Demographic Database. From Algorithms for Handwriting Recognition to Individual-Level Demographic and Socioeconomi... by Joana Maria Pujadas-Mora, Alícia Fornés, Oriol Ramos Terrades, Josep Lladós, Jialuo Chen, Miquel Valls-Fígols, Anna Cabré

“…Their construction uses artificial intelligence and computer vision methods as Handwriting Recognition to reduce the time of execution. …”
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AI-Based Screening Method for Early Identification of Invasive Ductal Carcinoma in Breast Cancer by Dominik Jánošík, Sila Yavuz

“…The objective of this work is to develop an efficient technique for the early recognition of breast cancer through precise and rapid screening, leveraging artificial intelligence (AI) in the medical field to minimize human error and enhance the likelihood of early intervention, thus potentially increasing life expectancy and reducing mortality rates. …”
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Accuracy comparison of Elamn and Jordan artificial neural networks for air particular matter concentration (PM 10) prediction using MODIS satellite images, a case study of Ahvaz. by javad sadidi, hani rezayan, Mohammad reza barshan

“…Due to the complexity of air pollution action, artificial intelligence models specifically, neural networks are utilized to simulate air pollution. …”
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Kinetic Analysis of the Thermal Decomposition of Polymer-Bonded Explosive Based on PETN: Model-Fitting Method and Isoconversional Method by Trung Toan Nguyen, Duc Nhan Phan, Van Thom Do, Hoang Nam Nguyen

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Adaptive Filtering for Channel Estimation in RIS-Assisted mmWave Systems by Shuying Shao, Tiejun Lv, Pingmu Huang

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Risk Assessment of Renewable Energy Power Systems via Graph Multi-Attention Networks by BAI Yunpeng, ZHANG Zhiyan, XU Cai, GUO Chuangxin, LIU Zhuping, ZHU Wenhao

“…Results，derived from integrating real-world data from a provincial power grid in China with that of the electrical power simulation system，demonstrate that the attention-based graph neural network method approach substantially improves the robustness and efficiency of risk assessments compared to other artificial intelligence methods. This approach shows considerable promise in renewable energy power systems for enhancing risk assessment.…”
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Advanced Techniques for Glucose Oxidase Immobilization: Evolution, Computational Integration, and Biomedical Applications by G Sreenivasulu, R. Ramakoteswara Rao

“…The study also explores future trends, including artificial intelligence and innovative support materials, to drive advancements in glucose oxidase immobilization. …”
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Modeling Compressive Strength of Self-Compacting Concrete (SCC) Using Novel Optimization Algorithm of AOA by Francisca Blanco, Ye Woo

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Me vs. the machine? Subjective evaluations of human- and AI-generated advice by Merrick R. Osborne, Erica R. Bailey

“…Abstract Artificial intelligence (“AI”) has the potential to vastly improve human decision-making. …”
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An Innovative Solution for Battery Draining in 5G Devices Using Alternate Routing Model by M. Sivasubramanian, J. Vignesh, V. Senthil kumar, S. Sumathi, R. Sathish, Kumar Parasuraman, B Santhosh Kumar, M Kathirvelu, Leena Bojaraj, Srihari K, Negasi Tsegay Sbhat

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Reinforcement Learning for Reconfigurable Robotic Soccer by M. Shameer Ahamed, J. J. J. Pey, S. M. Bhagya P. Samarakoon, M. A. Viraj J. Muthugala, Mohan Rajesh Elara

“…Robotic soccer is becoming more prevalent in competitions, furthering research in robotics and artificial intelligence. Reconfigurable robotics is used in application domains such as cleaning, multi-terrain locomotion, and logistical support, but reconfigurability has yet to be introduced in robotic soccer. …”
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Fingerprinting Indoor Positioning Based on Improved Sequential Deep Learning by Dongfang Mao, Haojie Lin, Xuyang Lou

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Deep Reinforcement Learning-Based Anti-Jamming Approach for Fast Frequency Hopping Systems by Sixi Cheng, Xiang Ling, Lidong Zhu

“…Increasing the hopping frequency speed and integrating artificial intelligence (AI) technologies are currently two of the most effective strategies for enhancing the anti-jamming performance of frequency hopping (FH) systems. …”
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