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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Discovering causal models for structural, construction and defense-related engineering phenomena by M.Z. Naser

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Digital twins in the building sector: Implementation and key features by Lemian Diana, Bode Florin

“…Additionally, the study addresses the benefits of advanced technologies such as big data, cloud computing, artificial intelligence (AI), and the Internet of Things (IoT) in enhancing BIM capabilities and supporting data-driven decision-making. …”
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Safety Autonomous Platform for Data-Driven Risk Management Based on an On-Site AI Engine in the Electric Power Industry by Dongyeop Lee, Daesik Lim, Joonwon Lee

“…It can automatically and precisely provide a safe and healthy working environment with the cooperation of safety mobility gateways (SMGs) according to the safety rule and risk index data created by the risk level of a current task, a worker profile, and the output of an on-site artificial intelligence (AI) engine in the SMGs. We practically implemented the proposed SAP architecture using the Hadoop ecosystem and verified its feasibility through a performance evaluation of the on-site AI engine and real-time operation of risk assessment and alarm notification for data-driven risk management.…”
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How digital transformation can influence workflows, teaching practices and curricula in (bio)process science and engineering—An interview series with stakeholders by J. F. Buyel

“…Abstract A massive digital transformation is underway in biotechnology and process engineering fueled by recent advances in machine learning and so‐called artificial intelligence, especially in the large language model field (e.g., ChatGPT). …”
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A GIS Based Unsteady Network Model and System Applications for Intelligent Mine Ventilation by Hui. Liu, Shanjun Mao, Mei. Li, Pingyang Lyu

“…With the development of state-of-the-art technology, such as the artificial intelligence and the Internet of Things, the construction of “intelligent mine” is being vigorously promoted, where the intelligent mine ventilation is one of the primary concerns that provides the efficient guarantee for safety production in the underground coal mine system. …”
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Machine Learning Classifiers and Data Synthesis Techniques to Tackle with Highly Imbalanced COVID-19 Data by Avaz Naghipour, Mohammad Reza Abbaszadeh Bavil Soflaei, mostafa ghader-zefrehei

“…We hope that this research will make a significant contribution to the current AI (Artificial Intelligence) efforts in combating the pandemic.…”
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LLM-driven multimodal target volume contouring in radiation oncology by Yujin Oh, Sangjoon Park, Hwa Kyung Byun, Yeona Cho, Ik Jae Lee, Jin Sung Kim, Jong Chul Ye

“…Inspired by the recent advancement of large language models (LLMs) that can facilitate the integration of the textural information and images, here we present an LLM-driven multimodal artificial intelligence (AI), namely LLMSeg, that utilizes the clinical information and is applicable to the challenging task of 3-dimensional context-aware target volume delineation for radiation oncology. …”
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Automatic speech recognition predicts contemporaneous earthquake fault displacement by Christopher W. Johnson, Kun Wang, Paul A. Johnson

“…The results demonstrate that earthquake faults emit seismic signatures in a similar manner to laboratory and numerical simulation faults, and artificial intelligence models developed for encoding audio of speech may have important applications in studying active fault zones.…”
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Synergy between Embedded and Non-Embedded Sensors in IoT Networks for Structural Health Monitoring of Concrete Structures: A Literature Review by Najem Oumayma, Benbrahim Mohammed, Kabbaj Mohammed Nabil, Boumhidi Jaouad

“…Structural Health Monitoring (SHM) is increasingly embraced thanks to advancements in the Internet of Things (IoT) and Artificial Intelligence (AI) being combined and infused. The main topics of this review are the foundations of SHM as a form of Non-intrusive evaluations and how it connects to the Internet of Things (IoT) for civil constructions. …”
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Introduction of smart technologies in event-management: socio-cultural aspect by V. A. Shelginskaya

“…The event industry is currently undergoing a period of active social change and technological innovation driven by the approach of the fourth industrial revolution and the advent of new methods of data processing by artificial intelligence. This could provide the meeting industry with new management capabilities related to the ability to predict and program visitor behavior based on the analysis of extremely large amounts of data about their behavior, thinking and preferences. …”
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IoT-based approach to multimodal music emotion recognition by Hanbing Zhao, Ling Jin

“…With the rapid development of Internet of Things (IoT) technology, multimodal emotion recognition has gradually become an important research direction in the field of artificial intelligence. However, existing methods often face challenges in efficiency and accuracy when processing multimodal data. …”
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Enhancing Fraud Detection in Banking With Deep Learning: Graph Neural Networks and Autoencoders for Real-Time Credit Card Fraud Prevention by Fawaz Khaled Alarfaj, Shabnam Shahzadi

“…Under the umbrella of artificial intelligence (AI), deep learning enables systems to cluster data and provide incredibly accurate results. …”
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Pattern Recognition of the Vertical Hydraulic Fracture Shapes in Coalbed Methane Reservoirs Based on Hierarchical Bi-LSTM Network by Zhaozhong Yang, Chenxi Yang, Xiaogang Li, Chao Min

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Advancements in the Application of Convolutional Neural Networks in Ultrasound Imaging for Breast Cancer Diagnosis and Treatment by An Zichen, Li Fan

“…Deep learning (DL), as one of the most powerful machine learning techniques in the field of artificial intelligence (AI), has the ability to automatically select features from raw data, achieving remarkable advancements in breast US imaging. …”
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Residual trio feature network for efficient super-resolution by Junfeng Chen, Mao Mao, Azhu Guan, Altangerel Ayush

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Toward cultural interpretability: A linguistic anthropological framework for describing and evaluating large language models by Graham M Jones, Shai Satran, Arvind Satyanarayan

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Advancements in training and deployment strategies for AI-based intrusion detection systems in IoT: a systematic literature review by S. Kumar Reddy Mallidi, Rajeswara Rao Ramisetty

“…This systematic literature review (SLR) explores the advancements in training and deployment strategies of Artificial Intelligence (AI) based IDS within IoT environments. …”
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Advanced ellipse overlap computation based on segment area of circles by Minhye Kim, Yongkuk Kim, Giphil Cho

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