THE IMPACT OF ARTIFICIAL INTELLIGENCE ON THE DEVELOPMENT OF PREDICTIVE COMPETENCE IN MODERN SPECIALISTS by Viacheslav Osadchyi, Maksym Pavlenko, Liliia Pavlenko, Oleksii Sysoiev, Vladyslav Kruglyk

“…At the same time, diverse adaptation patterns to AI use necessitate a rethinking of the role of human judgement and raise concerns about technological dependency, algorithmic bias, and unequal access to innovation. …”
Get full text

Enhanced Viral Genome Classification Using Large Language Models by Hemalatha Gunasekaran, Nesaian Reginal Wilfred Blessing, Umar Sathic, Mohammad Shahid Husain

“…Additionally, deep learning models like Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM) networks, and Bi-Directional LSTM networks are utilized for their robust capabilities in capturing complex patterns and dependencies within genomic sequences. …”
Get full text

AI-Driven Optimization of Blockchain Scalability, Security, and Privacy Protection by Fujiang Yuan, Zihao Zuo, Yang Jiang, Wenzhou Shu, Zhen Tian, Chenxi Ye, Junye Yang, Zebing Mao, Xia Huang, Shaojie Gu, Yanhong Peng

“…Artificial intelligence, with its powerful data processing capability, pattern recognition ability, and adaptive optimization algorithms, can improve the transaction processing efficiency of blockchain, enhance the security mechanism, and optimize the privacy protection strategy, thus effectively alleviating the limitations of blockchain in terms of scalability and security. …”
Get full text

Enhanced Fault Detection in Satellite Attitude Control Systems Using LSTM-Based Deep Learning and Redundant Reaction Wheels by Sajad Saraygord Afshari

Get full text

End-of-Line Quality Control Based on Mel-Frequency Spectrogram Analysis and Deep Learning by Jernej Mlinarič, Boštjan Pregelj, Gregor Dolanc

Get full text

Design and Dimension Optimization of Rigid–Soft Hand Function Rehabilitation Robots by Rui Zhang, Meng Ning, Yuqian Wang, Jun Yang

“…Experimental results confirm the system’s ability to replicate physiological motion patterns and adapt to multiple rehabilitation scenarios.…”
Get full text

A Novel Open Circuit Fault Diagnosis for a Modular Multilevel Converter with Modal Time-Frequency Diagram and FFT-CNN-BIGRU Attention by Ziyuan Zhai, Ning Wang, Siran Lu, Bo Zhou, Lei Guo

Get full text

Deploying an Educational Mobile Robot by Dorina Plókai, Borsa Détár, Tamás Haidegger, Enikő Nagy

Get full text

Numerical modelling of rope elasticity for heave compensation lifting in offshore crane operations by Bassey Asanga, Akanimo Ekpenyong, Aniekan Ikpe

Get full text

Large-scale gene expression data clustering through incremental ensemble approach by Imran Khan, Abdul Khalique Shaikh, Naresh Adhikari

Get full text

Advanced fault detection in photovoltaic panels using enhanced U-Net architectures by Khalfalla Awedat, Gurcan Comert, Mustafa Ayad, Abdulmajid Mrebit

Get full text

Deep(er) reconstruction of imaging Cherenkov detectors with swin transformers and normalizing flow models by C Fanelli, J Giroux, J Stevens

Get full text

Rapid Automated Mapping of Clouds on Titan With Instance Segmentation by Zachary Yahn, Douglas M. Trent, Ethan Duncan, Benoît Seignovert, John Santerre, Conor A. Nixon

“…On Titan, the largest moon of Saturn, tracking seasonal trends and weather patterns of clouds provides crucial insights into one of the most complex climates in the Solar System, yet much of the available image data are still analyzed in a conventional way. …”
Get full text

Analytical approach for modelling of thread crimp in jacquard woven two-dimensional fabrics by Brigita Kolcavová Sirková, Iva Mertová

“…The parameter responds both to changes in areas in the input image and to changes in the interlacing in the weave. An algorithm has been built in the ProTkaTex software that records the transition of both warp and weft threads in the pattern’s weave. …”
Get full text

Intelligent approach to detecting online fraudulent trading with solution for imbalanced data in fintech forensics by Saad M. Darwish, Amr Ibrahim Salama, Adel A. Elzoghabi

“…Abstract Detecting online fraudulent trading in the realm of Fintech presents several challenges, primarily due to the dynamic nature of financial markets and the evolving tactics of fraudsters. Traditional machine learning algorithms trained on unbalanced datasets tend to bias towards the majority class (legitimate transactions) and may overlook minority class (fraudulent transactions) patterns. …”
Get full text

An optimal federated learning-based intrusion detection for IoT environment by A. Karunamurthy, K. Vijayan, Pravin R. Kshirsagar, Kuan Tak Tan

“…This might reduce the detection performance of IDS as the system doesn’t have insightful knowledge about the new attack patterns. Analyzing and detecting intrusions by analyzing diverse attack patterns is complex for machine learning algorithms. …”
Get full text

Probing real sensory worlds of receivers with unsupervised clustering. by Michael Pfeiffer, Manfred Hartbauer, Alexander B Lang, Wolfgang Maass, Heinrich Römer

“…We apply a recently developed unsupervised machine learning algorithm based on probabilistic inference to find frequently occurring firing patterns in the response of the acoustic interneuron. …”
Get full text

A Multi-Epiphysiological Indicator Dog Emotion Classification System Integrating Skin and Muscle Potential Signals by Wenqi Jia, Yanzhi Hu, Zimeng Wang, Kai Song, Boyan Huang

“…Comprehensive feature extraction (time-domain, frequency-domain, nonlinearity) was conducted for each signal modality, and inter-emotional variance was analyzed to establish discriminative patterns. Four machine learning algorithms—Neural Networks (NN), Support Vector Machines (SVM), Gradient Boosting Decision Trees (GBDT), and XGBoost—were trained and evaluated, with XGBoost achieving the highest classification accuracy of 90.54%. …”
Get full text

Assessment of environmental impacts of armed conflict in Mozambique using remotely sensed data by Focas Francisco Bacar, Hilário Biché Faque

“…To evaluate these effects, we used Multi-temporal satellite images (Landsat 5 TM and Landsat 8 OLI-TIRS) in combination with fieldwork, geographic information systems, landscape ecology metrics, and the Random Forest machine learning algorithm. We also evaluated the spatiotemporal pattern of density of conflict events and landscape changes using the Kernel density estimator model. …”
Get full text

Integration of smart insoles for gait assessment in exoskeleton assisted rehabilitation by Luigi D’Arco, Haiying Wang, Huiru Zheng

“…Gait phases were identified using a Finite State Machine, with transitions guided by predictions from a fuzzy c-means clustering algorithm. …”
Get full text