Hybrid bio-inspired optimization based routing protocol for enhancing data transmission in clustered network by Kirandeep Kaur, Satinder Kaur

“…The Internet of Things (IoT) incorporates Wireless Sensor Networks (WSNs) to gather data in real time for a range of applications, including smart homes and healthcare. …”
Get full text

Limnological data derived from high frequency monitoring buoys are asynchronous in a large lake. by Claire Stevens, Paul C Frost, Nolan J T Pearce, James D Kelley, Arthur Zastepa, Marguerite A Xenopoulos

“…Our results show that if researchers intend to leverage these data to answer important questions and provide real-time applications related to environmental issues like harmful algal/cyanobacterial blooms, monitoring networks need to be designed carefully with spatial complexity in mind. …”
Get full text

Identification of AI-Generated Rock Thin-Section Images by Feature Analysis Under Data Scarcity by Magdalena Habrat, Maciej Dwornik

“…The results confirm the feasibility of building classifiers for synthetic images that could aid in detecting generated visual data in geological and petrographic research. They also serve as a foundation for further exploration of the importance of individual features in such applications.…”
Get full text

Real-Time Data-Driven Method for Bolt Defect Detection and Size Measurement in Industrial Production by Jinlong Yang, Chul-Hee Lee

“…To improve the model’s effectiveness across various industrial production environments, data augmentation techniques were employed, resulting in a trained model with notable precision, accuracy, and robustness. …”
Get full text

A Big Data Approach for the Regional-Scale Spatial Pattern Analysis of Amazonian Palm Locations by Matthew J. Drouillard, Anthony R. Cummings

“…Here, we utilize remotely sensed imagery in conjunction with topography and soil attribute data and employ a generalized cluster identification algorithm, Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN), to study the underlying patterns of palms in two areas of Guyana, South America. …”
Get full text

From archives to AI: Residential property data across three decades in Brunei DarussalamZenodo by Haziq Jamil, Amira Barizah Noorosmawie, Hafeezul Waezz Rabu, Lutfi Abdul Razak

“…The data set enables spatial and temporal analysis, with potential applications in economics, urban planning, and real estate research. …”
Get full text

A Staged Framework for Computer Vision Education: Integrating AI, Data Science, and Computational Thinking by In-Seong Jeon, Sukjae Joshua Kang, Seong-Joo Kang

“…Computer vision education is increasingly important in modern technology curricula; yet, it often lacks a systematic approach integrating both theoretical concepts and practical applications. This study proposes a staged framework for computer vision education designed to progressively build learners’ competencies across four levels. …”
Get full text

Federated Learning in Healthcare: A Benchmark Comparison of Engineering and Statistical Approaches for Structured Data Analysis by Siqi Li, Di Miao, Qiming Wu, Chuan Hong, Danny D’Agostino, Xin Li, Yilin Ning, Yuqing Shang, Ziwen Wang, Molei Liu, Huazhu Fu, Marcus Eng Hock Ong, Hamed Haddadi, Nan Liu

“…Our evaluation utilized both simulated data and real-world emergency department data, focusing on comparing both estimated model coefficients and the performance of model predictions. …”
Get full text

Data Augmentation and Deep Learning Methods for Pressure Prediction in Ignition Process of Solid Rocket Motors by Huixin Yang, Pengcheng Yu, Yan Cui, Bixuan Lou, Xiang Li

“…By comparison, the AGN-CBiLSTM method has a higher prediction accuracy with a percentage error of 3.27% between the predicted and actual data. This method provides an effective way to evaluate the performance of solid rocket motors and has a wide range of applications in the aerospace field.…”
Get full text

Characterizing Subsurface Structures From Hard and Soft Data With Multiple‐Condition Fusion Neural Network by Zhesi Cui, Qiyu Chen, Jian Luo, Xiaogang Ma, Gang Liu

“…Traditional subsurface characterization relies on two primary types of data: hard data, derived from direct subsurface measurements, and soft data, encompassing remotely sensed geophysical information and its interpretation. …”
Get full text

Enhancing drought prediction through machine learning: advanced techniques combining phenotypic and agrometeorological data by Efrem Yohannes Obsie, Yongguo Liu

“…Furthermore, our findings demonstrate the effectiveness and superior performance of the proposed method under various challenging data conditions, such as noise and occlusion, which hold great potential for real-world agricultural applications.…”
Get full text

Deep Learning-Based Detection of Depression and Suicidal Tendencies in Social Media Data with Feature Selection by İsmail Baydili, Burak Tasci, Gülay Tasci

“…Future work will focus on real-time detection capabilities and multilingual adaptation to enhance the practical applicability of the proposed approach.…”
Get full text

Order picking dataset from a warehouse of a footwear manufacturing companyMendeley Data by Rodrigo Furlan de Assis, William de Paula Ferreira, Mustapha Ouhimmou

“…This dataset originates from a real-world footwear manufacturing warehouse and provides a comprehensive foundation for benchmarking research in warehouse order-picking operations. Data was collected via SQL queries on the company’s Warehouse Management System (WMS), resulting in diverse formats such as CSV files, CAD layouts, and Python scripts. …”
Get full text

Indirect tuning of a complementary orientation filter using velocity data and a genetic algorithm by Dariusz Maton, John T. Economou, David Galvão Wall, Irfan Khan, Robert Cooper, David Ward, Simon Trythall

“…This results in increasing safety in applications such as firefighting and battlespace.…”
Get full text

Investigation of Spectral Variations in Different Solar Photovoltaic Modules Using Spaceborne and In-Situ Hyperspectral Data by Shoki Shimada, Hiroki Mizuochi, Wataru Takeuchi

“…The objective of this research was to investigate the detailed spectral data of four PV types currently on the market to enable their differentiation in hyperspectral satellite data. …”
Get full text

Extreme Space Weather Events of the Past 30 Years: Preparation for Data From Mission Vigil by Adam Majirský, Šimon Mackovjak, Silvia Kostárová, Samuel Amrich

“…For this reason, we prepared a pipeline for the community to obtain images and in‐situ measurements for these specific periods, allowing straightforward applications for the follow‐up data‐driven studies. This effort could maximize Vigil's potential. …”
Get full text

Simultaneous EEG-fNIRS Data Classification Through Selective Channel Representation and Spectrogram Imaging by Chayut Bunterngchit, Jiaxing Wang, Zeng-Guang Hou

“…However, existing research in this domain has grappled with the challenge of the efficient selection of features, resulting in the underutilization of the temporal richness of EEG and the spatial specificity of fNIRS data.To effectively address this challenge, this study proposed a deep learning architecture called the multimodal DenseNet fusion (MDNF) model that was trained on two-dimensional (2D) EEG data images, leveraging advanced feature extraction techniques. …”
Get full text

The integration of explainable AI in Educational Data Mining for student academic performance prediction and support system by Md. Mahmudul Islam, Farhad Hossain Sojib, Md. Fazle Hasan Mihad, Mahmudul Hasan, Mahfujur Rahman

“…To provide proper direction to students, we also developed a support system that uses the trained model from our analysis and provides recommendations and suggestions based on the input data. The further study integrates real-time data and mobile applications for the support system.…”
Get full text

A semantic segmentation framework with UNet-pyramid for landslide prediction using remote sensing data by Arush Kaushal, Ashok Kumar Gupta, Vivek Kumar Sehgal

“…Currently, Deep Learning is constrained by the lack of applicability, lack of data, and low efficiency in landslide detection but with recent advancement in deep learning-based solutions for landslide detection has sparked considerable advantages over traditional techniques. …”
Get full text

A Multimodal Framework for Advanced Cybersecurity Threat Detection Using GAN-Driven Data Synthesis by Nikolaos Peppes, Emmanouil Daskalakis, Theodoros Alexakis, Evgenia Adamopoulou

“…Traditional intrusion detection systems often struggle with detecting novel or rare attack types, particularly when data availability is limited or heterogeneous. The current study tries to address these challenges by proposing a unified, multimodal threat detection framework that leverages the combination of synthetic data generation through Generative Adversarial Networks (GANs), advanced ensemble learning, and transfer learning techniques. …”
Get full text