PREDICTIVE MAINTENANACE AND ITS ROLE IN ENERGY EFFICIENCY IN THE HOSPITALITY INDUSTRY by F. B. Adeleke, A. S Odetoye, E. E. Akerele, O. S. Folorunso, A. A. Bashiru

“…However, barriers such as high implementation expenses, insufficient technical expertise, and algorithmic biases continue to impede widespread adoption. …”
Get full text

Advanced Technologies for Smart Fertilizer Management in Agriculture: A Review by Jian-Jun Liu, Hao Wu, Imran Riaz

“…Future research directions highlight the need for integrating multi-sensor feedback loops, expanding open-access agronomic datasets, and advancing eco-friendly, AI-driven, and fully automated fertilization solutions. …”
Get full text

A Novel Ensemble of Deep Learning Approach for Cybersecurity Intrusion Detection with Explainable Artificial Intelligence by Abdullah Alabdulatif

“…This study presents a novel, hybrid ensemble learning-based intrusion detection framework that integrates deep learning and traditional ML algorithms with explainable artificial intelligence for real-time cybersecurity applications. …”
Get full text

An innovative approach to urban parks and perception: a cross-cultural analysis using big and small data by Siqi Lai, Brian Deal

“…Abstract Urban parks provide essential benefits that enhance human well-being and quality of life. This study integrates big data (online reviews, images) and small data (survey results) with large language models (LLMs) and object detection algorithms to analyze public perceptions of urban parks in Stockholm, New York, and Shanghai. …”
Get full text

Future impacts of artificial intelligence technologies in graphic design by Hussein Nasser Ibrahim Saleh Al-Dulaimi

“…Thanks to advanced algorithms and software, it has become possible to create innovative and attractive designs faster and easier than before. …”
Get full text

Machine learning based classification of catastrophic health expenditures: a cross-sectional study of Korean low-income households by Seok Min Ji, Jeewuan Kim, Kyu Min Kim

Get full text

Unveiling the art of video enhancement: a comprehensive examination of content selection and sequencing for optimal quality in conventional and AR/VR environments by Mehrunnisa, Mikolaj Leszczuk, Dawid Juszka

“…Compared to the current literature, challenges such as content selection variability, no standardized criteria, and limited data sets that serve as benchmarks must be considered. Integrating machine learning algorithms into data sets alongside scenario-based criteria can be an essential solution to such problems. …”
Get full text

REDalign: accurate RNA structural alignment using residual encoder-decoder network by Chun-Chi Chen, Yi-Ming Chan, Hyundoo Jeong

Get full text

Small Object Detection in UAV Remote Sensing Images Based on Intra-Group Multi-Scale Fusion Attention and Adaptive Weighted Feature Fusion Mechanism by Zhe Yuan, Jianglei Gong, Baolong Guo, Chao Wang, Nannan Liao, Jiawei Song, Qiming Wu

“…Experimental results indicate that the proposed IA-YOLOv8 model has a parameter quantity of 10.9 MB, attaining an average precision (mAP) value of 42.1% on the Visdrone2019 test set, an mAP value of 82.3% on the DIOR test set, and an mAP value of 39.8% on the AI-TOD test set. All these results outperform the existing detection algorithms, demonstrating the superior performance of the IA-YOLOv8 model in the task of small object detection for UAV remote sensing.…”
Get full text

A comparative study of deepfake facial manipulation technique using generative adversarial networks by Wasin Al Kishri, Jabar H. Yousif, Mahmood Al Bahri, Muhammad Zakarya, Naveed Khan, Sanad Sulaiman Al Maskari, Ahmet Gurhanli

“…Due to the development of image processing tools and visualization techniques integrating deep learning and artificial intelligence (AI) algorithms (in particular generative adversarial networks–GAN), this can pose serious threats to privacy and security. …”
Get full text

Predicting Diabetic Retinopathy and Nephropathy Complications Using Machine Learning Techniques by D. R. Manjunath, J. J. Lohith, S. Selva Kumar, Abhijit Das

Get full text

Automatic Subject Cataloguing at the German National Library by Christoph Poley, Sandro Uhlmann, Frank Busse, Jan-Helge Jacobs, Maximilian Kähler, Matthias Nagelschmidt, Markus Schumacher

“…Applied research activities in the DNB's AI project are closely related to the EMa ensuring that relevant scientific findings get integrated into its development. …”
Get full text

Recent advances and future technologies in nano-microplastics detection by Ajinkya Nene, Sorour Sadeghzade, Stefano Viaroli, Wenjie Yang, Ucheaga Paul Uchenna, Abhishek Kandwal, Xinghui Liu, Prakash Somani, Massimiliano Galluzzi

“…This work examines cutting-edge developments in nanotechnology-based detection, integrated spectro-microscopic techniques, and AI-driven classification algorithms, offering solutions to bridge gaps in NMP research. …”
Get full text

Geospatial brain-inspired navigation: a neurocognitive approach for autonomous systems in complex environments by Donghui Han, Tong Qin, Tianyu Yang, Hua Liao, Qiaosong Hei, Fangwen Yu, Bailu Si, Weihua Dong

“…To address these challenges, it is essential to explore the roles and functional connectivity of distinct brain regions involved in processing real-world geospatial information and integrate these insights into autonomous navigation algorithms. …”
Get full text

A comprehensive review of bibliometric and methodological approaches in flood mitigation studies: Current trends and future directions by Funmilayo Ebun Rotimi, Roohollah Kalatehjari, Taofeeq Durojaye Moshood, George Dokyi

Get full text

Deep learning-based time series prediction in multispectral and hyperspectral imaging for cancer detection by Lijun Hao, Changmin Wang, Jinshan Che, Mingming Sun, Yuhong Wang

“…Traditional approaches for cancer detection rely on handcrafted features and conventional machine learning algorithms, which struggle with high-dimensional spectral data, noise interference, and domain adaptation challenges. …”
Get full text

Prediction of Voice Therapy Outcomes Using Machine Learning Approaches and SHAP Analysis: A K-VRQOL-Based Analysis by Ji Hye Park, Ah Ra Jung, Ji-Na Lee, Ji-Yeoun Lee

“…These findings support the use of explainable artificial intelligence (AI) to enhance clinical decision-making and pave the way for personalized voice rehabilitation strategies.…”
Get full text

MFGC-Net: Bridging and Fusing Multiscale Features and Global Contexts for Multitask Sea Ice Fine Segmentation by Tianen Ma, Xinwei Chen, Linlin Xu, Pengfei Ma, Peilin Yu

“…However, the existing sea ice segmentation algorithms for SAR images often fail to consider long-range contextual dependencies when capturing multiscale features, resulting in an inability to fully exploit multiscale global contextual information. …”
Get full text

Method for Automatic Path Planning of Underwater Vehicles Considering Ambient Noise Fields by Gengming Zhang, Lihua Zhang, Yitao Wang, Chunyu Kang, Yinfei Zhou, Xiaodong Ma, Zeyuan Dai, Shaxige Wu

“…The method involves constructing a background noise spectrum level model using Automatic Identification System (AIS) data and wind speed data. Then, a Range-Dependent Acoustic Model (RAM) is integrated to generate a statistically significant 10th percentile noise field. …”
Get full text

Ensemble-based multiclass lung cancer classification using hybrid CNN-SVD feature extraction and selection method. by Md Sabbir Hossain, Niloy Basak, Md Aslam Mollah, Md Nahiduzzaman, Mominul Ahsan, Julfikar Haider

“…The extracted features were then processed by a set of ML algorithms along with a voting ensemble approach. Additionally, Gradient-weighted Class Activation Mapping (Grad-CAM) was integrated as an explainable AI (XAI) technique for enhancing model transparency by highlighting key influencing regions in the CT scans, which improved interpretability and ensured reliable and trustworthy results for clinical applications. …”
Get full text