Advancing soil mapping and management using geostatistics and integrated machine learning and remote sensing techniques: a synoptic review by Sunshine A. De Caires, Chaney St Martin, Melissa A. Atwell, Fuat Kaya, Glorious A. Wuddivira, Mark N. Wuddivira

“…Hybrid approaches combining geostatistics with ML algorithms (e.g., RF, Boost, SVM, ANN) demonstrate promise in addressing spatial uncertainty, while RS data enhances covariate enrichment and near-real-time applications. …”
Get full text

Flexible Configurable Modular Neural Network-Based OFDM Receiver by A. B. Sergienko, P. V. Apalina, A. D. Lebedinskaya

“…The proposed OFDM receiver for all considered modulation types provided error rates comparable to those of the baseline algorithms under favorable channel conditions (moderate delay spread with low Doppler spread) and outperformed baseline algorithms in severe conditions (channel with a large delay spread and high Doppler spread). …”
Get full text

Personalizing the Marketing with Artificial Intelligence (AI) by Rozhko Viktor I., Pletnova Yelyzaveta S.

“…Another major challenge is the technical limitations of AI. While AI algorithms are capable of analyzing vast amounts of data, they cannot always properly adapt to a changing market environment or predict consumer behavior in non-standard situations. …”
Get full text

Enhancing Security and Authenticity in Immersive Environments by Rebecca Acheampong, Dorin-Mircea Popovici, Titus Balan, Alexandre Rekeraho, Manuel Soto Ramos

“…Simulations of tampering and forgery attacks further validated the system’s capability to detect unauthorized modifications, with a 100% detection rate observed across multiple trials. While the system currently employs RSA, which may be vulnerable to quantum computing in the future, its modular design ensures crypto-agility, allowing for the integration of quantum-resistant algorithms as needed. …”
Get full text

Opportunities, challenges, and interventions for agriculture 4.0 adoption by Shanmugam Vijayakumar, Varunseelan Murugaiyan, S. Ilakkiya, Virender Kumar, Raman Meenakshi Sundaram, Rapolu Mahender Kumar

“…This includes developing cost-effective sensors, user-friendly algorithms, and versatile machinery tailored for small-scale farms. …”
Get full text

Clustering and classification of early knee osteoarthritis using machine-learning analysis of step-up and down test kinematics in recreational table tennis players by Ui-jae Hwang, Kyu Sung Chung, Sung-min Ha

“…Supervised learning models achieved high performance in classifying EOA status, with Random Forest, gradient boosting, and decision tree algorithms achieving 100% classification accuracy (AUC = 1.000) on the test dataset. …”
Get full text

The Author's Reply by Mohamad Reza Golzar Feshalami, Mehraban Shahi, Nasrin Davari Dolatabadi

“…The commenter rightly points out the need for a more detailed exploration of specific types of odontogenic tumors that present significant diagnostic challenges. While our article aimed to provide a broad overview of the diagnostic complexities across various tumor types, we acknowledge that a deeper dive into individual tumor characteristics and diagnostic hurdles would have enriched the discussion.Moving forward, we recognize the importance of focusing research efforts on developing AI algorithms that can effectively differentiate between different types of odontogenic tumors based on their unique clinical and radiographic features. …”
Get full text

Breast cancer diagnosis with MFF-HistoNet: a multi-modal feature fusion network integrating CNNs and quantum tensor networks by Tariq Mahmood, Tanzila Saba, Amjad Rehman

“…Leveraging the BreaKHis dataset, MFF-HistoNet differentiates between eight breast cancer subtypes and reduces model complexity while preserving the ability to capture vital spatial relationships, thus enhancing computational efficiency. …”
Get full text

The Nexus between spatiotemporal land use/land cover dynamics and ecosystem service values in the wabe river catchment, Omo Gibe River Basin, Ethiopia by Yonas Mathewos, Brook Abate, Mulugeta Dadi, Markos Mathewos

“…Historical Landsat imagery was classified under supervised techniques employing maximum likelihood algorithms in ERDAS Imagine; future changes were forecasted using multilayer perceptron neural network and cellular automata-Markov chain algorithms, and the value transfer valuation technique in conjunction with ArcGIS 10.8 was utilized to quantify the nexus between LULC changes and resulting ESVs. …”
Get full text

UOrtos: Methodology for Co-Registration and Subpixel Georeferencing of Satellite Imagery for Coastal Monitoring by Gonzalo Simarro, Daniel Calvete, Francesca Ribas, Yeray Castillo, Càrol Puig-Polo

“…The approach utilizes feature-based methods, cross-correlation, and RANSAC (RANdom SAmple Consensus) algorithms to accurately align images while avoiding outliers. …”
Get full text

The use of artificial intelligence in the HR processes of logistics companies by Adam Panek

“…Personalization of AI-based training improves employee engagement and productivity, while optimization of work schedules and accurate forecasting of staffing needs allow for better human resource management. …”
Get full text

Ensemble deep learning-enabled single-shot composite structured illumination microscopy (eDL-cSIM) by Jiaming Qian, Chunyao Wang, Hongjun Wu, Qian Chen, Chao Zuo

“…Experimental results demonstrate that eDL-cSIM integrates the advantages of various state-of-the-art neural networks, enabling robust super-resolution image predictions across different specimen types or structures of interest, and outperforms classical physics-driven methods in terms of imaging speed, reconstruction quality and environmental robustness, while avoiding intricate and specialized algorithmic procedures. …”
Get full text

Clinical Phenotype Identification and Validation of Patients with Sepsis in the Intensive Care Unit by GONG Chao, YU Na, CHEN Haoran

“…Then, supervised machine learning algorithms (lightweight gradient boosting machine) were used for the prediction of the patient's phenotypes, and were further combined with SHAP (Shapely Additive eXplanations) for the identification of important features. …”
Get full text

Deep Learning Frontiers in 3D Object Detection: A Comprehensive Review for Autonomous Driving by Ambati Pravallika, Mohammad Farukh Hashmi, Aditya Gupta

“…The progression of reference datasets, such as KITTI, Waymo, and NuScenes, was examined, emphasizing their crucial role in propelling detection algorithms forward and enabling comparative studies across diverse methodologies. …”
Get full text

Enhancing Security for Resource-Constrained Smart Cities IoT Applications: Optimizing Cryptographic Techniques with Effective Field Multipliers by Atef Ibrahim, Fayez Gebali

“…However, the limitations inherent in IoT edge nodes complicate the deployment of robust cryptographic algorithms, which are fundamentally reliant on finite-field multiplication operations. …”
Get full text

Visualized hysteroscopic artificial intelligence fertility assessment system for endometrial injury: an image-deep-learning study by Bohan Li, Hui Chen, Hua Duan

“…The incidence of AS in patients with infertility and recurrent miscarriage can be as high as 10%, while the pregnancy rate in cases of moderate to severe adhesions can be as low as 34%. …”
Get full text

Synthetic Data Generation for AI-Informed End-of-Line Testing for Lithium-Ion Battery Production by Tessa Krause, Daniel Nusko, Johannes Rittmann, Luciana Pitta Bauermann, Moritz Kroll, Carlo Holly

“…To make these predictions, we implement artificial intelligence algorithms to extract information from the measurements. …”
Get full text

Exploring Trends and Variability of Water Quality over Lake Titicaca Using Global Remote Sensing Products by Vann Harvey Maligaya, Analy Baltodano, Afnan Agramont, Ann van Griensven

“…Nowadays, remote sensing offers an alternative source of data to be used in water quality monitoring; by applying appropriate algorithms to satellite imagery, it is possible to retrieve water quality parameters. …”
Get full text

Innovative framework for fault detection and system resilience in hydropower operations using digital twins and deep learning by Jun Tan, Raoof Mohammed Radhi, Kimia Shirini, Sina Samadi Gharehveran, Zamen Parisooz, Mohsen Khosravi, Hossein Azarinfar

“…The integration of Digital Twins allowed for precise real-time modeling of system behavior, while Deep Learning algorithms effectively identified and predicted faults. …”
Get full text

Evaluation of the predictors of tooth loss using artificial intelligence-based machine learning approach: A retrospective study by Amit Rajabhau Pawar, Sankari Malaiappan, Pradeep Kumar Yadalam, P R Ganesh

“…Conclusion: By analyzing comprehensive datasets, machine learning models can enhance the accuracy and objectivity of tooth loss prediction. While challenges remain, such as data quality and privacy concerns, integrating machine learning algorithms in dentistry can revolutionize dental healthcare, improve patient outcomes, and reshape the future of periodontics.…”
Get full text