Automatic generation of AppArmor security policies based on large language models by SHA Yitian, LIU Shaojun, QIAN Xin, WU Yue, CHEN Peng, LIU Xing

“…Aimed at enhancing the process of generating security policies for AppArmor, an automated access control policy generation method was proposed based on large language models (LLM). …”
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AI Machine Learning–Based Diabetes Prediction in Older Adults in South Korea: Cross-Sectional Analysis by Hocheol Lee, Myung-Bae Park, Young-Joo Won

“…ResultsSignificant predictors of diabetes included hypertension (χ1Pχ1Pt3082Pt3082P ConclusionsThis study focused on modifiable risk factors, providing crucial data for establishing a system for the automated collection of health information and lifelog data from older adults using digital devices at service facilities.…”
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Association between Combined Structure Function Index and Glaucoma Severity by Shumpei Ogawa, Yoshimasa Tanabe, Yoshinori Itoh, Takahiko Noro, Hisato Gunji, Tadashi Nakano

“…The aim of this study was to investigate the relationship between combined structure function index (CSFI) and standard automated perimetry (SAP) parameters such as mean deviation (MD) and visual field index (VFI) in open-angle glaucoma (OAG). …”
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Innovative approaches for skin disease identification in machine learning: A comprehensive study by Kuldeep Vayadande, Amol A. Bhosle, Rajendra G. Pawar, Deepali J. Joshi, Preeti A. Bailke, Om Lohade

“…Investigate the effectiveness and performance of several algorithms, such as the flexible k-nearest neighbor, the sturdy support vector machine (SVM), and the complex convolutional neural networks (CNNs), advanced techniques for automated skin disease detection encompass deep learning methods such as recurrent neural networks (RNNs) for sequential data processing, generative adversarial networks (GANs) for generating synthetic data, and attention mechanisms for focusing on relevant image regions by means of a thorough examination of the most recent studies. …”
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Enhancing Photovoltaic Module Fault Diagnosis with Unmanned Aerial Vehicles and Deep Learning-Based Image Analysis by J. Jerome Vasanth, S. Naveen Venkatesh, V. Sugumaran, Vetri Selvi Mahamuni

“…Monitoring the condition of machineries and mechanical components for the presence of faults with the aid of image-based automated analysis is one major application of computer vision. …”
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Classification of Severity of Lung Parenchyma Using Saliency and Discrete Cosine Transform Energy in Computed Tomography of Patients With COVID-19 by Santiago Tello-Mijares, Francisco Flores, Fomuy Woo

“…This study proposes an automated system for assessing lung damage severity in coronavirus disease 2019 (COVID-19) patients using computed tomography (CT) images. …”
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An Approach to Predicting Energy Demand Within Automobile Production Using the Temporal Fusion Transformer Model by Andreas Lenk, Marcus Vogt, Christoph Herrmann

“…However, further improvements are still required for use in automated control of the energy system to reduce energy procurement costs. …”
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Current state and promise of user-centered design to harness explainable AI in clinical decision-support systems for patients with CNS tumors by Eric W. Prince, Eric W. Prince, Eric W. Prince, David M. Mirsky, David M. Mirsky, Todd C. Hankinson, Todd C. Hankinson, Carsten Görg, Carsten Görg

“…We also discuss how explainable AI tools, embedded in a human-centered decision-making process and different from fully automated solutions, can potentially enhance clinician performance. …”
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Initiation of the Dutch Inguinal Hernia Audit (DIHA): A survey on support for registration, obstacles, and possible areas of improvement by Richtje R. Meuzelaar, Floris P. J. den Hartog, Pieter J. Tanis, Anandi H. W. Schiphorst, Josephina P. J. Burgmans

“…Collecting these PROMs in a digital, automated format will facilitate successful implementation by minimizing administrative burden.…”
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A Superposed Epoch Analysis of Auroral Oval Coverage During Substorms Using Deep Learning‐Based Segmentation Models by Jia‐Nan Jiang, Zi‐Ming Zou, Yang Lu, Jia Zhong, Yong Wang, Yu‐Zhang Ma, Bian‐Long Zhao

“…However, the related studies were limited because of the absence of a reliable automated method to obtain auroral ovals from a large number of images. …”
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CodeContrast: A Contrastive Learning Approach for Generating Coherent Programming Exercises by Nicolás Torres

“…CodeContrast advances the automated generation of high-quality programming exercises, capturing relationships among programming components to enhance educational content and improve the learning experience for students and instructors.…”
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Deep Learning-Based Waste Classification with Transfer Learning Using EfficientNet-B0 Model by Risfendra Risfendra, Gheri Febri Ananda, Herlin Setyawan

“…Implementing this model in the industry can automate the waste sorting process more efficiently and accurately than methods based on inductive and capacitive proximity sensors. …”
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Gambaran Castelli’s Risk Index-1 pada Pasien Sindrom Koroner Akut di RSUP Dr. M. Djamil Padang by Eka Musmita Sabebegen, Rismawati Yaswir, Efrida Efrida

“…Colorimetric enzymatic method using automated clinical chemistry used to measure total cholesterol and HDL cholesterol. …”
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YOLO-TC: An Optimized Detection Model for Monitoring Safety-Critical Small Objects in Tower Crane Operations by Dong Ding, Zhengrong Deng, Rui Yang

“…This model holds significant promise for enhancing automated safety monitoring, potentially reducing occupational hazards by providing a proactive, resilient solution for real-time risk detection in tower crane operations.…”
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The Role of AMPS in Parkinson’s Disease Management: Scoping Review and Meta-Analysis by Roberto Tedeschi, Danilo Donati, Federica Giorgi

“…<b>Background:</b> Automated Mechanical Peripheral Stimulation (AMPS) is emerging as a potential therapeutic tool for managing motor and non-motor symptoms in individuals with Parkinson’s disease (PD), particularly in terms of improving gait, balance, and autonomic regulation. …”
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Long-term consequences of the Chornobyl disaster for aquatic ecosystems: A retrospective analysis and prognosis by R. Makhinko

“…A set of innovative measures to minimise negative consequences was proposed, including the use of nanotechnologies, genetically modified organisms, and automated monitoring systems. The need for international cooperation and the creation of a global database for long-term management of polluted aquatic ecosystems was substantiated. …”
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Discovering non-associated pressure-sensitive plasticity models with EUCLID by Haotian Xu, Moritz Flaschel, Laura De Lorenzis

“…Abstract We extend (EUCLID Efficient Unsupervised Constitutive Law Identification and Discovery)—a data-driven framework for automated material model discovery—to pressure-sensitive plasticity models, encompassing arbitrarily shaped yield surfaces with convexity constraints and non-associated flow rules. …”
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A novel wireless sensor network deployment for monitoring and predicting abnormal actions in medical environment and patient health state by R. Manikandan, S. Arunprakash, Rakan A. Alsowail, Tharani Pandiaraj

“…The system employs deep convolutional neural networks (DCNNs) and long short-term memory (LSTM) models to automate healthcare functions such as patient monitoring, infrastructure management, and disease prediction. …”
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Development of a handheld GPU-assisted DSC-TransNet model for the real-time classification of plant leaf disease using deep learning approach by Midhun P. Mathew, Sudheep Elayidom, V. P. Jagathy Raj, K. M. Abubeker

“…This research contributes to advancing the field of automated plant disease classification, addressing critical challenges in modern agriculture and promoting more efficient and sustainable farming practices.…”
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Realization and research of self-healing technology of power communication equipment based on power safety and controllability by Danni Liu, Song Zhang, Shengda Wang, Mingwei Zhou, Ji Du

“…Self-healing techniques address this need by automating fault identification and recovery. However, existing methods struggle with dynamic challenges like voltage fluctuations, thermal overloads, and multidimensional sensor data, often leading to delays in fault recovery and reduced safety. …”
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